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                                                          Machine learning from scratch pdf
   Book Description “What I cannot create, I do not understand” – Richard FeynmanThis book is your guide on your journey to deeper Machine Learning understanding by developing algorithms from scratch.But why this book?Step-by-step guide on how to approach, visualize and solve data science problemsLearn why and
   when Machine Learning is the right tool for the jobLearn how to process CSV, text, and image dataDevelop Linear Regression, Logistic Regression, Decision Tree, Neural Network, and other models. Use your models to solve real-world problems.Find how to improve low performing modelsLearn how to use Python
   libraries like NumPy, Pandas, Seaborn and moreComplete source code (notebooks) that works and runs in the cloud This book covers the building blocks of the most common methods in machine learning. This set of methods is like a toolbox for machine learning engineers. Those entering the field of machine learning
   should feel comfortable with this toolbox so they have the right tool for a variety of tasks. Each chapter in this book corresponds to a single machine learning method or group of methods. In other words, each chapter focuses on a single tool within the ML toolbox. In my experience, the best way to become comfortable
   with these methods is to see them derived from scratch, both in theory and in code. The purpose of this book is to provide those derivations. Each chapter is broken into three sections. The concept sections introduce the methods conceptually and derive their results mathematically. The construction sections show how
   to construct the methods from scratch using Python. The implementation sections demonstrate how to apply the methods using packages in Python like scikit-learn, statsmodels, and tensorflow. There are many great books on machine learning written by more knowledgeable authors and covering a broader range of
   topics. In particular, I would suggest An Introduction to Statistical Learning, Elements of Statistical Learning, and Pattern Recognition and Machine Learning, all of which are available online for free. While those books provide a conceptual overview of machine learning and the theory behind its methods, this book focuses
   on the bare bones of machine learning algorithms. Its main purpose is to provide readers with the ability to construct these algorithms independently. Continuing the toolbox analogy, this book is intended as a user guide: it is not designed to teach users broad practices of the field but rather how each tool works at a micro
   level. This book is for readers looking to learn new machine learning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common
   algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different algorithms create the models they do and the advantages and disadvantages of each one. This book will be most helpful for those with practice in basic modeling. It does
   not review best practices—such as feature engineering or balancing response variables—or discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models. The concept sections of this book primarily require knowledge of calculus, though some require an
   understanding of probability (think maximum likelihood and Bayes’ Rule) and basic linear algebra (think matrix operations and dot products). The appendix reviews the math and probabilityneeded to understand this book. The concept sections also reference a few common machine learning methods, which are
   introduced in the appendix as well. The concept sections do not require any knowledge of programming. The construction and code sections of this book use some basic Python. The construction sections require understanding of the corresponding content sections and familiarity creating functions and classes in Python.
   The code sections require neither. You can raise an issue here or email me at dafrdman@gmail.com. You can also connect with me on Twitter here or on LinkedIn here. Page 2 Ordinary Linear Regression The Loss-Minimization Perspective The Likelihood-Maximization Perspective Linear Regression Extensions
   Regularized Regression (Ridge and Lasso) Bayesian Regression Generalized Linear Models (GLMs) Discriminative Classification Logistic Regression The Perceptron Algorithm Fisher’s Linear Discriminant Generative Classification (Linear and Quadratic Discriminant Analysis, Naive Bayes) Decision Trees Regression
   Trees Classification Trees Tree Ensemble Methods Bagging Random Forests Boosting Neural Networks Welcome to the repo for my free online book, "Machine Learning from Scratch". The book itself can be found here. (A somewhat ugly version of) the PDF can be found in the book.pdf file above in the master branch.
   Note that JupyterBook is currently experimenting with the PDF creation. For suggested changes to the book, please create pull requests to the gh-pages branch! Any comments or questions are much appreciated, either here or via email at dafrdman@gmail.com. Thanks so much! Implementing machine learning
   algorithms from scratch. Algorithms implemented so far: Simple Linear Regression. Dataset: Stock data from Quandl Logistic Regression. Dataset: Stanford ML course dataset Naive Bayes Classifier. Dataset: Email spam/non-span Decision Trees K Nearest Neighbours. K Nearest Neighbours in Parallel. Dataset:
   Chronic Kidney disease data from UCI A-Star Algorithm K Means Clustering. K Means Clustering in Parallel. Dataset: IPL player stats norm data Support Vector Machine Page 2 Notifications Star 311 Fork 240 You can’t perform that action at this time. You signed in with another tab or window. Reload to refresh your
   session. You signed out in another tab or window. Reload to refresh your session. Thanks for your interest. Sorry, I do not support third-party resellers for my books (e.g. reselling in other bookstores). My books are self-published and I think of my website as a small boutique, specialized for developers that are deeply
   interested in applied machine learning. As such I prefer to keep control over the sales and marketing for my books. I’m sorry, I don’t support exchanging books within a bundle. The collections of books in the offered bundles are fixed. My e-commerce system is not sophisticated and it does not support ad-hoc bundles. I’m
   sure you can understand. You can see the full catalog of books and bundles here: Machine Learning Mastery Books If you have already purchased a bundle and would like to exchange one of the books in the bundle, then I’m very sorry, I don’t support book exchanges or partial refunds. If you are unhappy, please
   contact me directly and I can organize a refund. Thanks for your interest. I’m sorry,  I cannot create a customized bundle of books for you. It would create a maintenance nightmare for me. I’m sure you can understand. My e-commerce system is not very sophisticated. It cannot support ad-hoc bundles of books or the a la
   carte ordering of books. I do have existing bundles of books that I think go well together. You can see the full catalog of my books and bundles available here: Machine Learning Mastery Books Sorry, I don’t sell hard copies of my books. All of the books and bundles are Ebooks in PDF file format. This is intentional and I
   put a lot of thought into the decision: The books are full of tutorials that must be completed on the computer. The books assume that you are working through the tutorials, not reading passively. The books are intended to be read on the computer screen, next to a code editor. The books are playbooks, they are not
   intended to be used as references texts and sit the shelf. The books are updated frequently, to keep pace with changes to the field and APIs. I hope that explains my rationale. If you really do want a hard copy, you can purchase the book or bundle and create a printed version for your own personal use. There is no digital
   rights management (DRM) on the PDF files to prevent you from printing them. Sorry, I cannot create a purchase order for you or fill out your procurement documentation. You can complete your purchase using the self-service shopping cart with Credit Card or PayPal for payment. After you complete the purchase, I can
   prepare a PDF invoice for you for tax or other purposes. Sorry, no. I cannot issue a partial refund. It is not supported by my e-commerce system. If you are truly unhappy with your purchase, please contact me about getting a full refund. I stand behind my books, I know the tutorials work and have helped tens of
   thousands of readers. I am sorry to hear that you want a refund. Please contact me directly with your purchase details: Book Name: The name of the book or bundle that you purchased. Your Email: The email address that you used to make the purchase (note, this may be different to the email address you used to pay
   with via PayPal). Order Number: The order number in your purchase receipt email. I will then organize a refund for you. I would love to hear why the book is a bad fit for you. Anything that you can tell me to help improve my materials will be greatly appreciated. I have a thick skin, so please be honest. Sample chapters
   are provided for each book. Each book has its own webpage, you can access them from the catalog. On each book’s page, you can access the sample chapter. Find the section on the book’s page titled “Download Your Sample Chapter“. Click the link, provide your email address and submit the form. Check your email,
   you will be sent a link to download the sample. If you have trouble with this process or cannot find the email, contact me and I will send the PDF to you directly. Yes. I can provide an invoice that you can use for reimbursement from your company or for tax purposes. Please contact me directly with your purchase details:
   The name of the book or bundle that you purchased. The email address that you used to make the purchase. Ideally, the order number in your purchase receipt email. Your full name/company name/company address that you would like to appear on the invoice. I will create a PDF invoice for you and email it back. Sorry,
   I no longer distribute evaluation copies of my books due to some past abuse of the privilege. If you are a teacher or lecturer, I’m happy to offer you a student discount. Contact me directly and I can organize a discount for you. Sorry, I do not offer Kindle (mobi) or ePub versions of the books. The books are only available
   in PDF file format. This is by design and I put a lot of thought into it. My rationale is as follows: I use LaTeX to layout the text and code to give a professional look and I am afraid that EBook readers would mess this up. The increase in supported formats would create a maintenance headache that would take a large
   amount of time away from updating the books and working on new books. Most critically, reading on an e-reader or iPad is antithetical to the book-open-next-to-code-editor approach the PDF format was chosen to support. My materials are playbooks intended to be open on the computer, next to a text editor and a
   command line. They are not textbooks to be read away from the computer. Sorry, all of my books are self-published and do not have ISBNs. Thanks for your interest in my books I’m sorry that you cannot afford my books or purchase them in your country. I don’t give away free copies of my books. I do give away a lot of
   free material on applied machine learning already. You can access the best free material here: Maybe. I offer a discount on my books to: Students Teachers Retirees If you fall into one of these groups and would like a discount, please contact me and ask. Sorry, the books and bundles are for individual purchase only. I
   do not respond to RFIs or similar. Maybe. I support payment via PayPal and Credit Card. You may be able to set up a PayPal account that accesses your debit card. I recommend contacting PayPal or reading their documentation. Sorry no. I do not support WeChat Pay or Alipay at this stage. I only support payment via
   PayPal and Credit Card. Yes, you can print the purchased PDF books for your own personal interest. There is no digital rights management (DRM) on the PDFs to prevent you from printing them. Please do not distribute printed copies of your purchased books. You can review the table of contents for any book. I provide
   two copies of the table of contents for each book on the book’s page. Specifically: A written summary that lists the tutorials/lessons in the book and their order. A screenshot of the table of contents taken from the PDF. If you are having trouble finding the table of contents, search the page for the section titled “Table of
   Contents”. No. I only support payment via PayPal or Credit Card. Yes. If you purchase a book or bundle and later decide that you want to upgrade to the super bundle, I can arrange it for you. Contact me and let me know that you would like to upgrade and what books or bundles you have already purchased and which
   email address you used to make the purchases. I will create a special offer code that you can use to get the price of books and bundles purchased so far deducted from the price of the super bundle. I am happy for you to use parts of my material in the development of your own course material, such as lecture slides for
   an in person class or homework exercises. I am not happy if you share my material for free or use it verbatim. This would be copyright infringement. All code on my site and in my books was developed and provided for educational purposes only. I take no responsibility for the code, what it might do, or how you might use
   it. If you use my material to teach, please reference the source, including: The Name of the author, e.g. “Jason Brownlee”. The Title of the tutorial or book. The Name of the website, e.g. “Machine Learning Mastery”. The URL of the tutorial or book. The Date you accessed or copied the code. For example: Jason
   Brownlee, Machine Learning Algorithms in Python, Machine Learning Mastery, Available from  accessed April 15th, 2018. Also, if your work is public, contact me, I’d love to see it out of general interest. Thanks for asking. Sorry, no. I prefer to keep complete control over my content for now. Sorry no. My books are self-
   published and are only available from my website. Generally no. I don’t have exercises or assignments in my books. I do have end-to-end projects in some of the books, but they are in a tutorial format where I lead you through each step. The book chapters are written as self-contained tutorials with a specific learning
   outcome. You will learn how to do something at the end of the tutorial. Some books have a section titled “Extensions” with ideas for how to modify the code in the tutorial in some advanced ways. They are like self-study exercises. Sorry, I do not offer a certificate of completion for my books or my email courses. Sorry,
   new books are not included in your super bundle. I release new books every few months and develop a new super bundle at those times. All existing customers will get early access to new books at a discount price. Note, that you do get free updates to all of the books in your super bundle. This includes bug fixes,
   changes to APIs and even new chapters sometimes. I send out an email to customers for major book updates or you can contact me any time and ask for the latest version of a book. No. I have books that do not require any skill in programming, for example: Machine Learning Mastery With Weka Master Machine
   Learning Algorithms Other books do have code examples in a given programming language. You must know the basics of the programming language, such as how to install the environment and how to write simple programs. I do not teach programming, I teach machine learning for developers. You do not need to be a
   good programmer. That being said, I do offer tutorials on how to setup your environment efficiently and even crash courses on programming languages for developers that may not be familiar with the given language. No. My books do not cover the theory or derivations of machine learning methods. This is by design. My
   books are focused on the practical concern of applied machine learning. Specifically, how algorithms work and how to use them effectively with modern open source tools. If you are interested in the theory and derivations of equations, I recommend a machine learning textbook. Some good examples of machine learning
   textbooks that cover theory include: I generally don’t run sales. If I do have a special, such as around the launch of a new book, I only offer it to past customers and subscribers on my email list. I do offer book bundles that offer a discount for a collection of related books. I do offer a discount to students, teachers, and
   retirees. Contact me to find out about discounts. Sorry, I don’t have videos. I only have tutorial lessons and projects in text format. This is by design. I used to have video content and I found the completion rate much lower. I want you to put the material into practice. I have found that text-based tutorials are the best way
   of achieving this. With text-based tutorials you must read, implement and run the code. With videos, you are passively watching and not required to take any action. Videos are entertainment or infotainment instead of productive learning and work. After reading and working through the tutorials you are far more likely to
   use what you have learned. Yes, I offer a 90-day no questions asked money-back guarantee. I stand behind my books. They contain my best knowledge on a specific machine learning topic, and each book as been read, tested and used by tens of thousands of readers. Nevertheless, if you find that one of my Ebooks is
   a bad fit for you, I will issue a full refund. There are no physical books, therefore no shipping is required. All books are EBooks that you can download immediately after you complete your purchase. I support purchases from any country via PayPal or Credit Card. Yes. I recommend using standalone Keras version 2.4 (or
   higher) running on top of TensorFlow version 2.2 (or higher). All tutorials on the blog have been updated to use standalone Keras running on top of Tensorflow 2. All books have been updated to use this same combination. I do not recommend using Keras as part of TensorFlow 2 yet (e.g. tf.keras). It is too new, new
   things have issues, and I am waiting for the dust to settle. Standalone Keras has been working for years and continues to work extremely well. There is one case of tutorials that do not support TensorFlow 2 because the tutorials make use of third-party libraries that have not yet been updated to support TensorFlow 2.
   Specifically tutorials that use Mask-RCNN for object recognition. Once the third party library has been updated, these tutorials too will be updated. The book “Long Short-Term Memory Networks with Python” is not focused on time series forecasting, instead, it is focused on the LSTM method for a suite of sequence
   prediction problems. The book “Deep Learning for Time Series Forecasting” shows you how to develop MLP, CNN and LSTM models for univariate, multivariate and multi-step time series forecasting problems. Mini-courses are free courses offered on a range of machine learning topics and made available via email, PDF
   and blog posts. Mini-courses are: Short, typically 7 days or 14 days in length. Terse, typically giving one tip or code snippet per lesson. Limited, typically narrow in scope to a few related areas. Ebooks are provided on many of the same topics providing full training courses on the topics. Ebooks are: Longer, typically 25+
   complete tutorial lessons, each taking up to an hour to complete. Complete, providing a gentle introduction into each lesson and includes full working code and further reading. Broad, covering all of the topics required on the topic to get productive quickly and bring the techniques to your own projects. The mini-courses
   are designed for you to get a quick result. If you would like more information or fuller code examples on the topic then you can purchase the related Ebook. The book “Master Machine Learning Algorithms” is for programmers and non-programmers alike. It teaches you how 10 top machine learning algorithms work, with
   worked examples in arithmetic, and spreadsheets, not code. The focus is on an understanding on how each model learns and makes predictions. The book “Machine Learning Algorithms From Scratch” is for programmers that learn by writing code to understand. It provides step-by-step tutorials on how to implement top
   algorithms as well as how to load data, evaluate models and more. It has less on how the algorithms work, instead focusing exclusively on how to implement each in code. The two books can support each other. The books are a concentrated and more convenient version of what I put on the blog. I design my books to be
   a combination of lessons and projects to teach you how to use a specific machine learning tool or library and then apply it to real predictive modeling problems. The books get updated with bug fixes, updates for API changes and the addition of new chapters, and these updates are totally free. I do put some of the book
   chapters on the blog as examples, but they are not tied to the surrounding chapters or the narrative that a book offers and do not offer the standalone code files. With each book, you also get all of the source code files used in the book that you can use as recipes to jump-start your own predictive modeling problems. My
   books are playbooks. Not textbooks. They have no deep explanations of theory, just working examples that are laser-focused on the information that you need to know to bring machine learning to your project. There is little math, no theory or derivations. My readers really appreciate the top-down, rather than bottom-up
   approach used in my material. It is the one aspect I get the most feedback about. My books are not for everyone, they are carefully designed for practitioners that need to get results, fast. A code file is provided for each example presented in the book. Dataset files used in each chapter are also provided with the book.
   The code and dataset files are provided as part of your .zip download in a code/ subdirectory. Code and datasets are organized into subdirectories, one for each chapter that has a code example. If you have misplaced your .zip download, you can contact me and I can send an updated purchase receipt email with a link
   to download your package. Ebooks can be purchased from my website directly. First, find the book or bundle that you wish to purchase, you can see the full catalog here: Machine Learning Mastery Books Click on the book or bundle that you would like to purchase to go to the book’s details page. Click the “Buy Now”
   button for the book or bundle to go to the shopping cart page. Fill in the shopping cart with your details and payment details, and click the “Place Order” button. After completing the purchase you will be emailed a link to download your book or bundle. All prices are in US dollars (USD). Books can be purchased with
   PayPal or Credit Card. All prices on Machine Learning Mastery are in US dollars. Payments can be made by using either PayPal or a Credit Card that supports international payments (e.g. most credit cards). You do not have to explicitly convert money from your currency to US dollars. Currency conversion is performed
   automatically when you make a payment using PayPal or Credit Card. After filling out and submitting your order form, you will be able to download your purchase immediately. Your web browser will be redirected to a webpage where you can download your purchase. You will also receive an email with a link to download
   your purchase. If you lose the email or the link in the email expires, contact me and I will resend the purchase receipt email with an updated download link. After you complete your purchase you will receive an email with a link to download your bundle. The download will include the book or books and any bonus material.
   To use a discount code, also called an offer code, or discount coupon when making a purchase, follow these steps: 1. Enter the discount code text into the field named “Discount Coupon” on the checkout page. Note, if you don’t see a field called “Discount Coupon” on the checkout page, it means that that product does
   not support discounts. 2. Click the “Apply” button. 3. You will then see a message that the discount was applied successfully to your order. Note, if the discount code that you used is no longer valid, you will see a message that the discount was not successfully applied to your order. There are no physical books, therefore
   no shipping is required. All books are EBooks that you can download immediately after you complete your purchase. I recommend reading one chapter per day. Momentum is important. Some readers finish a book in a weekend. Most readers finish a book in a few weeks by working through it during nights and
   weekends. You will get your book immediately. After you complete and submit the payment form, you will be immediately redirected to a webpage with a link to download your purchase. You will also immediately be sent an email with a link to download your purchase. What order should you read the books? That is a
   great question, my best suggestions are as follows: Consider starting with a book on a topic that you are most excited about. Consider starting with a book on a topic that you can apply on a project immediately. Also, consider that you don’t need to read all of the books, perhaps a subset of the books will get you the skills
   you need or want. Nevertheless, one suggested order for reading the books is as follows: Probability for Machine Learning Statistical Methods for Machine Learning Linear Algebra for Machine Learning Master Machine Learning Algorithms Machine Learning Algorithms From Scratch Machine Learning Mastery With
   Weka Machine Learning Mastery With Python Machine Learning Mastery With R Data Preparation for Machine Learning Imbalanced Classification With Python Time Series Forecasting With Python Ensemble Learning Algorithms With Python XGBoost With Python Deep Learning With Python Long Short-Term Memory
   Networks with Python Deep Learning for Natural Language Processing Deep Learning for Computer Vision Deep Learning for Time Series Forecasting Better Deep Learning Generative Adversarial Networks with Python I hope that helps. Sorry, I do not have a license to purchase my books or bundles for libraries. The
   books are for individual use only. Generally, no. Multi-seat licenses create a bit of a maintenance nightmare for me, sorry. It takes time away from reading, writing and helping my readers. If you have a big order, such as for a class of students or a large team, please contact me and we will work something out. I update
   the books frequently and you can access the latest version of a book at any time. In order to get the latest version of a book, contact me directly with your order number or purchase email address and I can resend your purchase receipt email with an updated download link. I do not maintain a public change log or errata
   for the changes in the book, sorry. There are no physical books, therefore no delivery is required. All books are Ebooks in PDF format that you can download immediately after you complete your purchase. You will receive an email with a link to download your purchase. You can also contact me any time to get a new
   download link. I support purchases from any country via PayPal or Credit Card. My best advice is to start with a book on a topic that you can use immediately. Baring that, pick a topic that interests you the most. If you are unsure, perhaps try working through some of the free tutorials to see what area that you gravitate
   towards. Start Here in Machine Learning Generally, I recommend focusing on the process of working through a predictive modeling problem end-to-end: Applied Machine Learning Process I have three books that show you how to do this, with three top open source platforms: These are great places to start. You can
   always circle back and pick-up a book on algorithms later to learn more about how specific methods work in greater detail. Thanks for your interest. You can see the full catalog of my books and bundles here: Machine Learning Mastery Full Catalog  Thanks for asking. I try not to plan my books too far into the future. I try
   to write about the topics that I am asked about the most or topics where I see the most misunderstanding. If you would like me to write more about a topic, I would love to know. Contact me directly and let me know the topic and even the types of tutorials you would love for me to write. Contact me and let me know the
   email address (or email addresses) that you think you used to make purchases. I can look up what purchases you have made and resend purchase receipts to you so that you can redownload your books and bundles. All prices are in US Dollars (USD). All currency conversion is handled by PayPal for PayPal purchases,
   or by Stripe and your bank for credit card purchases. It is possible that your link to download your purchase will expire after a few days. This is a security precaution. Please contact me and I will resend you purchase receipt with an updated download link. The book “Deep Learning With Python” could be a prerequisite
   to”Long Short-Term Memory Networks with Python“. It teaches you how to get started with Keras and how to develop your first MLP, CNN and LSTM. The book “Long Short-Term Memory Networks with Python” goes deep on LSTMs and teaches you how to prepare data, how to develop a suite of different LSTM
   architectures, parameter tuning, updating models and more. Both books focus on deep learning in Python using the Keras library. The book “Long Short-Term Memory Networks in Python” focuses on how to develop a suite of different LSTM networks for sequence prediction, in general. The book “Deep Learning for Time
   Series Forecasting” focuses on how to use a suite of different deep learning models (MLPs, CNNs, LSTMs, and hybrids) to address a suite of different time series forecasting problems (univariate, multivariate, multistep and combinations). The LSTM book teaches LSTMs only and does not focus on time series. The Deep
   Learning for Time Series book focuses on time series and teaches how to use many different models including LSTMs. The book “Long Short-Term Memory Networks With Python” focuses on how to implement different types of LSTM models. The book “Deep Learning for Natural Language Processing” focuses on how
   to use a variety of different networks (including LSTMs) for text prediction problems. The LSTM book can support the NLP book, but it is not a prerequisite. You may need a business or corporate tax number for “Machine Learning Mastery“, the company, for your own tax purposes. This is common in EU companies for
   example. The Machine Learning Mastery company is operated out of Puerto Rico. As such, the company does not have a VAT identification number for the EU or similar for your country or regional area. The company does have a Company Number. The details are as follows: Company Name: Zeus LLC Company
   Number: 421867-1511 Linux, MacOS, and Windows. There are no code examples in “Master Machine Learning Algorithms“, therefore no programming language is used. Algorithms are described and their working is summarized using basic arithmetic. The algorithm behavior is also demonstrated in excel spreadsheets,
   that are available with the book. It is a great book for learning how algorithms work, without getting side-tracked with theory or programming syntax. If you are interested in learning about machine learning algorithms by coding them from scratch (using the Python programming language), I would recommend a different
   book: Machine Learning Algorithms From Scratch: With Python I write the content for the books (words and code) using a text editor, specifically sublime. I typeset the books and create a PDF using LaTeX. All of the books have been tested and work with Python 3 (e.g. 3.5 or 3.6). Most of the books have also been
   tested and work with Python 2.7. Where possible, I recommend using the latest version of Python 3. After you fill in the order form and submit it, two things will happen: You will be redirected to a webpage where you can download your purchase. You will be sent an email (to the email address used in the order form) with
   a link to download your purchase. The redirect in the browser and the email will happen immediately after you complete the purchase. You can download your purchase from either the webpage or the email. If you cannot find the email, perhaps check other email folders, such as the “spam” folder? If you have any
   concerns, contact me and I can resend your purchase receipt email with the download link. I do test my tutorials and projects on the blog first. It’s like the early access to ideas, and many of them do not make it to my training. Much of the material in the books appeared in some form on my blog first and is later refined,
   improved and repackaged into a chapter format. I find this helps greatly with quality and bug fixing. The books provide a more convenient packaging of the material, including source code, datasets and PDF format. They also include updates for new APIs, new chapters, bug and typo fixing, and direct access to me for all
   the support and help I can provide. I believe my books offer thousands of dollars of education for tens of dollars each. They are months if not years of experience distilled into a few hundred pages of carefully crafted and well-tested tutorials. I think they are a bargain for professional developers looking to rapidly build
   skills in applied machine learning or use machine learning on a project. Also, what are skills in machine learning worth to you? to your next project? and you’re current or next employer? Nevertheless, the price of my books may appear expensive if you are a student or if you are not used to the high salaries for developers
   in North America, Australia, UK and similar parts of the world. For that, I am sorry. Discounts I do offer discounts to students, teachers and retirees. Please contact me to find out more. Free Material I offer a ton of free content on my blog, you can get started with my best free material here: Start Here for Machine
   Learning About my Books My books are playbooks. They are intended for developers who want to know how to use a specific library to actually solve problems and deliver value at work. My books guide you only through the elements you need to know in order to get results. My books are in PDF format and come with
   code and datasets, specifically designed for you to read and work-through on your computer. My books give you direct access to me via email (what other books offer that?) My books are a tiny business expense for a professional developer that can be charged to the company and is tax deductible in most regions. Very
   few training materials on machine learning are focused on how to get results. The vast majority are about repeating the same math and theory and ignore the one thing you really care about: how to use the methods on a project. Comparison to Other Options Let me provide some context for you on the pricing of the
   books: There are free videos on youtube and tutorials on blogs. Great, I encourage you to use them, including my own free tutorials. There are very cheap video courses that teach you one or two tricks with an API. My books teach you how to use a library to work through a project end-to-end and deliver value, not just a
   few tricks A textbook on machine learning can cost $50 to $100. All of my books are cheaper than the average machine learning textbook, and I expect you may be more productive, sooner. A bootcamp or other in-person training can cost $1000+ dollars and last for days to weeks. A bundle of all of my books is far
   cheaper than this, they allow you to work at your own pace, and the bundle covers more content than the average bootcamp. Sorry, my books are not available on websites like Amazon.com. I carefully decided to not put my books on Amazon for a number of reasons: Amazon takes 65% of the sale price of self-published
   books, which would put me out of business. Amazon offers very little control over the sales page and shopping cart experience. Amazon does not allow me to contact my customers via email and offer direct support and updates. Amazon does not allow me to deliver my book to customers as a PDF, the preferred format
   for my customers to read on the screen. I hope that helps you understand my rationale. I am sorry to hear that you’re having difficulty purchasing a book or bundle. I use Stripe for Credit Card and PayPal services to support secure and encrypted payment processing on my website. Some common problems when
   customers have a problem include: Perhaps you can double check that your details are correct, just in case of a typo? Perhaps you could try a different payment method, such as PayPal or Credit Card? Perhaps you’re able to talk to your bank, just in case they blocked the transaction? I often see customers trying to
   purchase with a domestic credit card or debit card that does not allow international purchases. This is easy to overcome by talking to your bank. If you’re still having difficulty, please contact me and I can help investigate further. When you purchase a book from my website and later review your bank statement, it is
   possible that you may see an additional small charge of one or two dollars. The charge does not come from my website or payment processor. Instead, the charge was added by your bank, credit card company, or financial institution. It may be because your bank adds an additional charge for online or international
   transactions. This is rare but I have seen this happen once or twice before, often with credit cards used by enterprise or large corporate institutions. My advice is to contact your bank or financial institution directly and ask them to explain the cause of the additional charge. If you would like a copy of the payment
   transaction from my side (e.g. a screenshot from the payment processor), or a PDF tax invoice, please contact me directly. I give away a lot of content for free. Most of it in fact. It is important to me to help students and practitioners that are not well off, hence the enormous amount of free content that I provide. You can
   access the free content: On the blog On the start here page I have thought very hard about this and I sell machine learning Ebooks for a few important reasons: I use the revenue to support the site and all the non-paying customers. I use the revenue to support my family so that I can continue to create content.
   Practitioners that pay for tutorials are far more likely to work through them and learn something. I target my books towards working professionals that are more likely to afford the materials. Yes. All updates to the book or books in your purchase are free. Books are usually updated once every few months to fix bugs, typos
   and keep abreast of API changes. Contact me anytime and check if there have been updates. Let me know what version of the book you have (version is listed on the copyright page). Yes. Please contact me anytime with questions about machine learning or the books. One question at a time please. Also, each book
   has a final chapter on getting more help and further reading and points to resources that you can use to get more help. Yes, the books can help you get a job, but indirectly. Getting a job is up to you. It is a matching problem between an organization looking for someone to fill a role and you with your skills and
   background. That being said, there are companies that are more interested in the value that you can provide to the business than the degrees that you have. Often, these are smaller companies and start-ups. You can focus on providing value with machine learning by learning and getting very good at working through
   predictive modeling problems end-to-end. You can show this skill by developing a machine learning portfolio of completed projects. My books are specifically designed to help you toward these ends. They teach you exactly how to use open source tools and libraries to get results in a predictive modeling project. machine
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