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Showing 4 outstanding Python books published on
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Python for ArcGIS Pro: Automate cartography and data analysis using ArcPy, ArcGIS API for Python, Notebooks, and pandas

by Silas Toms

Integrating Python into your day-to-day ArcGIS work is highly recommended when dealing with large amounts of geospatial data. Python for ArcGIS Pro aims to help you get your work done faster, with greater repeatability and higher confidence in your results. Starting from programming basics and building in complexity, two experienced ArcGIS professionals-turned-Python programmers teach you how to incorporate scripting at each step: automating the production of maps for print, managing data between ArcGIS Pro and ArcGIS Online, creating custom script tools for sharing, and then running data analysis and visualization on top of the ArcGIS geospatial library, all using Python.
Published on : April 29, 2022
Python version: TH
586 pages

Practical Fraud Prevention: Fraud and AML Analytics for Fintech and eCommerce, Using SQL and Python

by Gilit Saporta

Over the past two decades, the booming e-commerce and fintech industries have become a breeding ground for fraud. Organizations that conduct business online are constantly engaged in a cat-and-mouse game with these invaders. In this practical book, Gilit Saporta and Shoshana Maraney draw on their fraud-fighting experience to provide best practices, methodologies, and tools to help you detect and prevent fraud and other malicious activities.
Published on : April 26, 2022
Python version: TH
394 pages

Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python

by Kunal Sawarkar

PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implement PyTorch Lightning models to get up to speed in no time.
Published on : April 29, 2022
Python version: TH
364 pages

Distributed Machine Learning with Python: Accelerating model training and serving with distributed systems

by Guanhua Wang

Reducing time costs in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time.
Published on : April 29, 2022
Python version: TH
284 pages