Learn how to transform data into business insight with these Data Tutorials and eBooks.
Deep Reinforcement Learning Hands-On By Maxim Lapan
This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.
Key Features of the book:
- Explore deep reinforcement learning (RL), from the first principles to the latest algorithms
- Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms
- Keep up with the very latest industry developments, including AI-driven chatbots
About the Author:
Maxim Lapan is a deep learning enthusiast and independent researcher with 15 years’ work expertise as a software developer and a systems architect lays from low-level Linux kernel driver development to performance optimization and design of distributed applications working on thousands of servers.
Advanced Analytics and Real-Time Data Processing in Apache Spark [Video] By Tomasz Lelek
Filled with hands-on examples, this course will help you perform data analysis and take you from an intermediate level to an advanced approach to data analytics.
What You Will Learn:
- Real-time data streaming processes and operations with Spark Streaming
- Implement high-velocity streaming and data processing use cases while working with streaming API
- Dive into MLlib– the machine learning functional library in Spark with highly scalable algorithms
- ]Createmachine learning pipelines to combine multiple algorithms in a single workflow
- Understand graphs and the Apache Spark API for graphs—GraphX
- Apply interesting graph algorithms and graph processing with GraphX in a distributed environment
- Use R, the popular statistical language, to work with Spark—SparkR
- See how SparkR allows users to create and transform RDDs in R
- See analytical use case implementations using MLLib, GraphX, and Spark Streaming
Hands-On Data Science with Anaconda By Dr. Yuxing Yan, James Yan
Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda
- This book is your step-by-step guide full of use cases, examples and illustrations to get you well-versed with the concepts of Anaconda
- The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more
- You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows
- You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod
- Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them
Data Visualization in Python by Examples [Video] By Harish Garg
Create visualizations for your data sets using tools in Python
This friendly course takes you through data visualization in Python using matplotlib, ggplot, seaborn, and plotly. It is packed with step-by-step instructions and working examples.
This comprehensive course is divided into clear bite-size chunks so you can learn at your own pace and focus on the areas of most interest to you.
Key features of the video:
- Use data visualization as your preferred business reporting tool
- Add impact to your data by representing information in the form of a chart, diagram, pictures, and so on
- Deploy plots and charts using various data visualization tools in Python
