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Thoughtful Data Science: A Programmer's Toolset for Data Analysis and Artificial Intelligence with Python, Jupyter Notebook, and PixieDust
Thoughtful Data Science: A Programmer's Toolset for Data Analysis and Artificial Intelligence with Python, Jupyter Notebook, and PixieDust

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
  • Discover the best tools that...
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Data Analysis with Python: A Modern Approach
Data Analysis with Python: A Modern Approach

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.

Key Features

  • Bridge your data analysis...
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data
Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Understand, explore, and effectively present data using the powerful data visualization techniques of Python

Key Features

  • Use the power of Pandas and Matplotlib to easily solve data mining issues
  • Understand the basics of statistics to build powerful predictive data...
Hands-On Deep Learning for Images with TensorFlow: Build intelligent computer vision applications using TensorFlow and Keras
Hands-On Deep Learning for Images with TensorFlow: Build intelligent computer vision applications using TensorFlow and Keras

Explore TensorFlow's capabilities to perform efficient deep learning on images

Key Features

  • Discover image processing for machine vision
  • Build an effective image classification system using the power of CNNs
  • Leverage TensorFlow's capabilities to...
Mastering Exploratory Analysis with pandas: Build an end-to-end data analysis workflow with Python
Mastering Exploratory Analysis with pandas: Build an end-to-end data analysis workflow with Python

Explore Python frameworks like pandas, Jupyter notebooks, and Matplotlib to build data pipelines and data visualization

Key Features

  • Learn to set up data analysis pipelines with pandas and Jupyter notebooks
  • Effective techniques for data selection, manipulation, and...
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition

Skip the theory and get the most out of Tensorflow to build production-ready machine learning models

Key Features

  • Exploit the features of Tensorflow to build and deploy machine learning models
  • Train neural networks to tackle real-world problems in Computer Vision and...
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras
Generative Adversarial Networks Projects: Build next-generation generative models using TensorFlow and Keras

Explore various Generative Adversarial Network architectures using the Python ecosystem

Key Features

  • Use different datasets to build advanced projects in the Generative Adversarial Network domain
  • Implement projects ranging from generating 3D shapes to a face aging...
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python
Hands-On Automated Machine Learning: A beginner's guide to building automated machine learning systems using AutoML and Python

Automate data and model pipelines for faster machine learning applications

Key Features

  • Build automated modules for different machine learning components
  • Understand each component of a machine learning pipeline in depth
  • Learn to use different open source...
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
Deep Learning Quick Reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras

Dive deeper into neural networks and get your models trained, optimized with this quick reference guide

Key Features

  • A quick reference to all important deep learning concepts and their implementations
  • Essential tips, tricks, and hacks to train a variety of deep learning...
Ethereum Cookbook: Over 100 recipes covering Ethereum-based tokens, games, wallets, smart contracts, protocols, and Dapps
Ethereum Cookbook: Over 100 recipes covering Ethereum-based tokens, games, wallets, smart contracts, protocols, and Dapps

Mine Ether, deploy smart contracts, tokens, and ICOs, and manage security vulnerabilities of Ethereum

Key Features

  • Build end-to-end decentralized Ethereum apps using Truffle, Web3, and Solidity
  • Explore various solution-based recipes to build smart contracts and foolproof...
Julia 1.0 Programming: Dynamic and high-performance programming to build fast scientific applications, 2nd Edition
Julia 1.0 Programming: Dynamic and high-performance programming to build fast scientific applications, 2nd Edition

Enter the exciting world of Julia, a high-performance language for technical computing

Key Features

  • Leverage Julia's high speed and efficiency for your applications
  • Work with Julia in a multi-core, distributed, and networked environment
  • Apply Julia to...
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