menu
{ "item_title" : "Deep Learning for Physics Research", "item_author" : [" Erdmann Martin "], "item_description" : "A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/81/123/745/981123745X_b.jpg", "price_data" : { "retail_price" : "98.00", "online_price" : "98.00", "our_price" : "98.00", "club_price" : "98.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Deep Learning for Physics Research|Erdmann Martin

Deep Learning for Physics Research

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.

This item is Non-Returnable

Details

  • ISBN-13: 9789811237454
  • ISBN-10: 981123745X
  • Publisher: World Scientific Publishing Company
  • Publish Date: July 2021
  • Dimensions: 9 x 6 x 0.81 inches
  • Shipping Weight: 1.37 pounds
  • Page Count: 340

Related Categories

You May Also Like...

    1

BAM Customer Reviews