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Design and Analysis of Algorithms: A Contemporary Perspective April 30, 2019 by Sandeep Sen (Author), Amit Kumar (Author) Paperback: 350 pages Publisher: Cambridge University Press (May 31, 2019) Language: English ISBN-10: 1108721990 ISBN-13: 978-1108721998

TensorFlow Reinforcement Learning Quick Start Guide: Get up and running with training and deploying intelligent, self-learning agents using Python Author: Kaushik Balakrishnan Pub Date: 2019 ISBN: 978-1789533583 Pages: 184 Language: English Format: EPUB Size: 11 Mb

Effective TypeScript: Writing Typed JavaScript that Scales 预发布版 Author: Dan Vanderkam Publisher: by O’Reilly Media Edition： January 2020 Type: epub, azw3, pdf

Hands-On Predictive Analytics with Python: Master the complete predictive analytics process, from problem definition to model deployment Author: Alvaro Fuentes Publisher: Packet Pub Date: Dec. 2018 ISBN: 978-1789138719 Pages: 330 Language: English Format: EPUB Size: 14 Mb 内含相关code压缩包 ----------------- Chapters Details: Chapter 1, The Predictive Analytics Process, presents the foundational concepts of the field, explains at a high level the different stages in the predictive analytics process, and gives an overview of the libraries we will use in the book. Chapter 2, Problem Understanding and Data Preparation, introduces the problems and datasets we will be using throughout the book and shows the basics of how to collect and prepare a dataset for modeling. Chapter 3, Dataset Understanding – Exploratory Data Analysis, shows how to get important information from a dataset using visualizations and other numerical techniques. Chapter 4, Predicting Numerical Values with Machine Learning, introduces the main ideas and concepts of machine learning and some of the most popular regression models. Chapter 5, Predicting Categories with Machine Learning, introduces some of the most important classification machine learning models. Chapter 6, Introducing Neural Nets for Predictive Analytics, shows how to build neural network models. These have become very popular because they are very powerful and are capable of producing highly accurate models.  Chapter 7, Model Evaluation, shows the main metrics and approaches you need to evaluate how good the predictions produced by a predictive model are.” “Chapter 6, Introducing Neural Nets for Predictive Analytics, shows how to build neural network models. These have become very popular because they are very powerful and are capable of producing highly accurate models.  Chapter 7, Model Evaluation, shows the main metrics and approaches you need to evaluate how good the predictions produced by a predictive model are. Chapter 8, Model Tuning and Improving Performance, presents important techniques such as K-fold cross-validation that will improve the performance of our predictive model. Chapter 9, Implementing a Model with Dash, shows how to build an interactive web application that will take input from the user and will use a trained predictive model to provide predictions.”

Hands-On Recommendation Systems with Python: Start building powerful and personalized, recommendation engines with Python Rounak Banik 201807 Packt Publishing

Hands-On Natural Language Processing with Python: A practical guide to applying deep learning architectures to your NLP applications Rajesh Arumugam, Rajalingappaa Shanmugamani Packt Publishing, July 2018

“Practical Convolutional Neural Networks: Implement advanced deep learning models using Python” Md. Rezaul Karim,Mohit Sewak,Pradeep Pujari 2018年2月 epub文件，内含示例源码

Use React and React Native to build applications for desktop browsers, mobile browsers, and even as native mobile apps

Build modular applications that are easy to scale using the most powerful components and design patterns that React can offer you right now

Machine Learning Paradigms Artificial Immune Systems and their Applications in Software Personalization authors: Dionisios N. Sotiropoulos • George A. Tsihrintzis

Data Visualization with Python and JavaScript 2017-03-17: Second Release

Python Data Science Handbook Essential Tools for Working with Data

Mastering-TypeScript-second-edition 该版本升级到ts 2.0版

angular 2 router 2017年3月出版

angular 核心成员 Victor Savkin 新作，主要介绍angular 2 router，在其个人主页可以见到关于本书的一些介绍 Victor Savkin 主要负责angular2的DI， CD，表单，和路由开发 First published: March 2017

SVG Animations From Common UX Implementations to Complex Responsive Animation

Angular Cookbook published by Packt, 2017 目录 Chapter 1, Strategies for Upgrading to Angular 2 Chapter 2, Conquering Components and Directives Chapter 3, Building Template-Driven and Reactive Forms Chapter 4, Mastering Promises and still play a crucial role. Chapter 5, ReactiveX Observables Chapter 6, The Component Router Chapter 7, Services, Dependency Injection, and NgModule Chapter 8, Application Organization and Managemen Chapter 9, Angular 2 Testing Chapter 10, Performance and Advanced Concepts

M(ongoDB)E(xpress)R(eact)N(ode)全栈开发

Angular 2 From Theory To Practice

update to the angular 2, ti also import the typescript

Reactive Programming with Node.js

Thoughtful Machine Learning with Python A Test-Driven Approach

模型识别与机器学习Christopher M. Bishop:Pattern Recognition and Machine Learning