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Practical Data Science with R, Second Edition
Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.
Practices of the Python Pro
With Practices of the Python Pro, you'll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python. You'll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly useful techniques that will help you code like a pro.
Python Workout
In Python Workout, author Reuven M. Lerner guides you through 50 carefully selected exercises that invite you to flex your programming muscles. As you take on each new challenge, you'll build programming skill and confidence. The thorough explanations help you lock in what you've learned and apply it to your own projects.
R in Action
R in Action, Second Edition presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods.
Reactive Data Handling
Reactive Data Handling is a collection of five hand-picked chapters introducing you to building reactive applications capable of handling real-time processing with large data loads. You'll start with the high-level architecture of reactive applications and then look at low-level practical aspects.
Real-World Machine Learning
Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems.
Think Like a Data Scientist
Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data
Tiny Python Projects
A long journey is really a lot of little steps. The same is true when you're learning Python, so you may as well have some fun along the way! Written in a lighthearted style with entertaining exercises that build powerful skills, Tiny Python Projects takes you from amateur to Pythonista as you create 22 bitesize programs.
Deep Learning Crash Course
In this liveVideo course, machine learning expert Oliver Zeigermann teaches you the basics of deep learning. With Oliver Zeigermann's crystal-clear video instruction and the hands-on exercises in this video course, you'll get started in deep learning using open-source Python-friendly tools like scikit-learn and Keras, and TensorFlow 2.0 (soon to be officially released with exciting new updates!).
Keras in Motion
Keras in Motion teaches you to build neural-network models for real-world data problems using Python and Keras. In over two hours of hands-on, practical video lessons, you'll apply Keras to common machine learning scenarios, ranging from regression and classification to implementing Autoencoders and applying transfer learning.