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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits
Author Tarek Amr
Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsKey FeaturesDelve into machine learning with this comprehensive guide to scikit-learn and scientific Python Mast....
Release Date 2020/07 -
The Deep Learning with PyTorch Workshop
Author Hyatt Saleh
Get a head start in the world of AI and deep learning by developing your skills with PyTorchKey FeaturesLearn how to define your own network architecture in deep learning Implement helpful methods to create and train a model using PyTorch syntax Discover how intelligent....
Release Date 2020/07 -
Machine Learning for Algorithmic Trading - Second Edition
Author Stefan Jansen
Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio.Key FeaturesDesign, train, and evaluate machine lea....
Release Date 2020/07 -
The Machine Learning Workshop - Second Edition
Author Hyatt Saleh
Take a comprehensive and step-by-step approach to understanding machine learningKey FeaturesDiscover how to apply the scikit-learn uniform API in all types of machine learning models Understand the difference between supervised and unsupervised learning models Reinforce....
Release Date 2020/07 -
Author Mirza Rahim Baig , Thomas V. Joseph , Nipun Sadvilkar
Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret textKey FeaturesUnderstand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognitio....
Release Date 2020/07 -
Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases
Author Alok Kumar , Mayank Jain
Use ensemble learning techniques and models to improve your machine learning results.Ensemble Learning for AI Developers starts you at the beginning with an historical overview and explains key ensemble techniques and why they are needed. You then will learn ho....
Release Date 2020/06 -
Hands-On Mathematics for Deep Learning
Author Jay Dawani
A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networks Learn the mat....
Release Date 2020/06 -
Hands-On Machine Learning with C++
Author Kirill Kolodiazhnyi
Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasetsKey FeaturesBecome familiar with data processing, performance measuri....
Release Date 2020/05 -
Hands-On Python Deep Learning for the Web
Author Anubhav Singh , Sayak Paul
Use the power of deep learning with Python to build and deploy intelligent web applicationsKey FeaturesCreate next-generation intelligent web applications using Python libraries such as Flask and Django Implement deep learning algorithms and techniques for performing sma....
Release Date 2020/05 -
Author Michael Pawlus , Rodger Devine
Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and DeepnetKey FeaturesUnderstand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specif....
Release Date 2020/04 -
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
Author Anubhav Singh , Rimjhim Bhadani
Learn how to deploy effective deep learning solutions on cross-platform applications built using TensorFlow Lite, ML Kit, and FlutterKey FeaturesWork through projects covering mobile vision, style transfer, speech processing, and multimedia processing Cover interesting d....
Release Date 2020/04 -
Mastering Azure Machine Learning
Author Christoph Korner , Kaijisse Waaijer
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and KubernetesKey FeaturesMake sense of data on the cloud by implementing advanced analytics Train and optimize advanced....
Release Date 2020/04 -
Hands-On One-shot Learning with Python
Author Shruti Jadon , Ankush Garg
Get to grips with building powerful deep learning models using PyTorch and scikit-learnKey FeaturesLearn how you can speed up the deep learning process with one-shot learning Use Python and PyTorch to build state-of-the-art one-shot learning models Explore architectures....
Release Date 2020/04 -
Machine Learning for iOS Developers
Author Abhishek Mishra
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner!Machine earning (ML) is the science of getting computers to act without being explicitly programmed....
Release Date 2020/03 -
Deep Reinforcement Learning in Action
Author Brandon Brown , Alexander Zai
Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you’ll master foundational and advanced DRL techniques by taking on interesting challenges lik....
Release Date 2020/03 -
Author Paolo Perrotta
You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It's easy to be intimidated, even as a software developer. The good news is that it doesn't have to be tha....
Release Date 2020/03 -
Hands-On Machine Learning with ML.NET
Author Jarred Capellman
Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET CoreKey FeaturesGet well-versed with the ML.NET framework and its components and APIs using practical examples Learn....
Release Date 2020/03 -
PyTorch Computer Vision Cookbook
Author Michael Avendi
Discover powerful ways to use deep learning algorithms and solve real-world computer vision problems using PythonKey FeaturesSolve the trickiest of problems in computer vision by combining the power of deep learning and neural networks Leverage PyTorch 1.x capabilities t....
Release Date 2020/03 -
Author Francesco Esposito , Dino Esposito
Master machine learning concepts and develop real-world solutionsMachine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the fo....
Release Date 2020/02 -
Author Stanley Bileschi , Shanqing Cai , Eric Nielsen
In Deep Learning with JavaScript, you’ll learn to use TensorFlow.js to build deep learning models that run directly in the browser. This fast-paced book, written by Google engineers, is practical, engaging, and easy to follow. Through diverse examples featurin....
Release Date 2020/02 -
Author Swarna Gupta , Rehan Ali Ansari , Dipayan Sarkar
Tackle the complex challenges faced while building end-to-end deep learning models using modern R librariesKey FeaturesUnderstand the intricacies of R deep learning packages to perform a range of deep learning tasks Implement deep learning techniques and algorithms for r....
Release Date 2020/02 -
The Supervised Learning Workshop - Second Edition
Author Blaine Bateman , Ashish Ranjan Jha , Benjamin Johnston
Cut through the noise and get real results with a step-by-step approach to understanding supervised learning algorithmsKey FeaturesIdeal for those getting started with machine learning for the first time A step-by-step machine learning tutorial with exercises and activit....
Release Date 2020/02 -
Advanced Deep Learning with TensorFlow 2 and Keras - Second Edition
Author Rowel Atienza
Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and KerasKey FeaturesExplore the most advanced deep learning techniques that drive modern AI results New coverage of unsupervised deep learning using mutual informatio....
Release Date 2020/02 -
Building Machine Learning Powered Applications
Author Emmanuel Ameisen
Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers....
Release Date 2020/01 -
Author Richard Nichol , Doug Hudgeon
Machine Learning for Business teaches business-oriented machine learning techniques you can do yourself. Concentrating on practical topics like customer retention, forecasting, and back office processes, you’ll work through six projects that help you form an ML-for....
Release Date 2020/01 -
Hands-On Music Generation with Magenta
Author Alexandre DuBreuil
Design and use machine learning models for music generation using Magenta and make them interact with existing music creation toolsKey FeaturesLearn how machine learning, deep learning, and reinforcement learning are used in music generation Generate new content by....
Release Date 2020/01 -
Deep Reinforcement Learning Hands-On - Second Edition
Author Maxim Lapan
New edition of the bestselling guide to deep reinforcement learning and how it's used to solve complex real-world problems. Revised and expanded to include multi-agent methods, discrete optimization, RL in robotics, advanced exploration techniques, and moreKey Fea....
Release Date 2020/01 -
Hands-On Reinforcement Learning for Games
Author Micheal Lanham
Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlowKey FeaturesGet to grips with the different reinforcement and DRL algorithms for game development Learn how to implement component....
Release Date 2020/01 -
Foundations of Deep Reinforcement Learning: Theory and Practice in Python
Author Wah Loon Keng , Laura Graesser
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and PracticeDeep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In ....
Release Date 2019/12 -
Machine Learning and Big Data with kdb+/q
Author Jan Novotny , Paul A. Bilokon , Aris Galiotos
Upgrade your programming language to more effectively handle high-frequency data Machine Learning and Big Data with KDB+/Q offers quants, programmers and algorithmic traders a practical entry into the powerful but non-intuitive kdb+ database and q programming language. Id....
Release Date 2019/12