Bridge the gap between developer and data scientist by creating a modern open-source, Python-based toolset that works with Jupyter Notebook, and PixieDust.
Key Features
Think deeply as a developer about your strategy and toolset in data science
Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis.
Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for...
Use Python's built-in features to create innovative graphics for data visualization and technical illustrations. This book goes beyond simple commands and libraries to explain how to not only display but also rotate, shade, and edit graphics for any purpose.
Starting with the essential Python functions to set up a...
Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-world problem.
All code in MATLAB Machine Learning Recipes: A Problem-Solution Approach is executable....
