BOOKS - PROGRAMMING - Applied Deep Learning Design and implement your own Neural Netw...
Applied Deep Learning Design and implement your own Neural Networks to solve real-world problems - Dr. Rajkumar Tekchandani, Dr. Neeraj Kumar 2023 RETAIL PDF BPB Publications BOOKS PROGRAMMING
ECO~23 kg CO²

2 TON

Views
15487

Telegram
 
Applied Deep Learning Design and implement your own Neural Networks to solve real-world problems
Author: Dr. Rajkumar Tekchandani, Dr. Neeraj Kumar
Year: 2023
Pages: 624
Format: RETAIL PDF
File size: 27.0 MB
Language: ENG



Pay with Telegram STARS
''

You may also be interested in:

Understanding Deep Learning
Math for Deep Learning
Learning Deep Architectures for AI
Deep Learning and the Game of Go
The Science of Deep Learning
The Little Book of Deep Learning
Deep Learning with Python
Understanding Deep Learning
Deep Learning in Biometrics
Deep Learning for Engineers
Deep Learning in Practice
Deep Learning Algorithms
Deep Learning for Engineers
Deep Learning For Dummies
Regularization in Deep Learning
Deep Learning for Search
Deep Learning on Graphs
Kubernetes Secrets Handbook: Design, implement, and maintain production-grade Kubernetes Secrets management solutions
Applied Text Analysis with Python Enabling Language Aware Data Products with Machine Learning
Applied Machine Learning for Smart Data Analysis (Computational Intelligence in Engineering Problem Solving)
Applied Machine Learning Solutions with Python Production-ready ML Projects Using Cutting-edge Libraries
Python Programming, Deep Learning: 3 Books in 1: A Complete Guide for Beginners, Python Coding for AI, Neural Networks, and Machine Learning, Data Science Analysis … Learners (Python Programming
Learn OpenCV with Python by Examples Implement Computer Vision Algorithms Provided by OpenCV with Python for Image Processing, Object Detection and Machine Learning 2nd Edition
Masters Level Teaching, Learning and Assessment: Issues in Design and Delivery (Teaching and Learning, 10)
Applied Op Amp Circuits: Analysis and Design with NI(R) Multisim(TM) (Energy Systems in Electrical Engineering)
Applied Embedded Electronics Design Essentials for Robust Systems (4th Early Release)
Deep Learning for 3D Point Clouds
Hands-On Deep Learning with Tensorflow
Deep Learning A Practical Introduction
Deep Learning A Practical Introduction
Deep Reinforcement Learning in Action
Blockchain and Deep Learning for Smart
Deep Learning Through the Prism of Tensors
Deep Learning Patterns and Practices
Deep Learning for Video Understanding
Math and Architectures of Deep Learning
Deep Learning: Foundations and Concepts
Mathematics of Deep Learning: An Introduction
Deep Learning: A Practical Introduction
Deep Reinforcement Learning in Action