Data Science

tldr: Don't read this if all you want is from tensroflow import keras

With the rise of Data Science and Machine Learning, Data Engineering is quickly becoming a in-demand skill. Data Engineering requires a unique skillset that is hard to learn without experience. I will teach you how to write scalable data pipelines and more!

Learn how to analyze big datasets in a distributed environment without being bogged down by theoretical topics. The API is vast and other learning tools make the mistake of trying to cover everything. This book only covers what you need to know, so you can explore other parts of the API on your own!

Contains reprinted articles in full color (including more than 230 figures) from 16 volumes of Memory Dump Analysis Anthology (Diagnomicon) related to pattern-oriented software diagnostics with additional comments showing the historical development of this autonomous and distinctive discipline over the last 18 years.

This book will help you easily build beautiful plots in Python using the powerful plotnine package, which has been adapted from the popular ggplot2 package in R. If you'd like to create highly customised plots, including replicating the styles of XKCD and fivethirtyeight, this is your book.

This book brings the fundamentals of Machine Learning to you, using tools and techniques used to solve real-world problems in Computer Vision, Natural Language Processing, and Time Series analysis. The skills taught in this book will lay the foundation for you to advance your journey to Machine Learning Mastery!

The second edition of Getting Started with Data Journalism - updated, with expanded sections, as well as new examples and exercises. This new edition brings the book up to date because, while the basic skills needed for data journalism have not changed, the tools and techniques have evolved since the first edition of this book was published.

General trace and log analysis patterns allow the application of uniform diagnostics and anomaly detection across diverse software environments. This pattern language covers any execution artifact from a small debugging trace to a distributed log with billions of messages from hundreds of computers, thousands of components, threads, and processes.

Learn to use R, the tidyverse collection of packages and functional programming concepts to write efficient and readable code.

Lots of pundits and researchers have ideas about how education data work should be done and who should do it. Many of their ideas are disseminated widely. This book covers the things those books do not: metadata, working with enterprise IT, data requests, politics, and why descriptive statistics can take you far.

Build Machine Learning models (especially Deep Neural Networks) that you can easily integrate with existing or new web apps. Think of your ReactJs, Vue, or Angular app enhanced with the power of Machine Learning models.

A primer on RStudio, Git, and GitHub.

The "Voice of Foreign Exchange™" is a series of 8 expert advisors reinventing the "Elliott Wave Theory" and other popular trading methods using modern communications formula. This is Volume I in the Expert Advisor Series. This book has the source code for 2 expert advisors and the Voice over Foreign Exchange™ (Vo4X) engine.

Want to know about data mining? This book will help you to do data mining using Weka and RapidMiner.