Complete Guide to TensorFlow for Deep Learning with Python
MP4 | Video: 1280x720 | Duration: 14 Hours | 2.3 GB | Subtitles: VTT | Source Files
Author: Jose Portilla | Language: English | Skill level: All Levels
Learn how to use Google's Deep Learning Framework - TensorFlow with Python !

This course will guide you through how to use Google's TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow framework in a way that is easy to understand. Other courses and tutorials have tended to stay away from pure tensorflow and instead use abstractions that give the user less control. Here we present a course that finally serves as a complete guide to using the TensorFlow framework as intended, while showing you the latest techniques available in deep learning!

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google. Become a machine learning guru today! We'll see you inside the course.

What you'll learn:
Understand how Neural Networks Work
Build your own Neural Network from Scratch with Python
Use TensorFlow for Classification and Regression Tasks
Use TensorFlow for Image Classification with Convolutional Neural Networks
Use TensorFlow for Time Series Analysis with Recurrent Neural Networks
Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders
Learn how to conduct Reinforcement Learning with OpenAI Gym
Create Generative Adversarial Networks with TensorFlow
Become a Deep Learning Guru!








Download link:
Kod:
nitroflare_com: http://nitroflare.com/view/4938C866F798074/htbpn.Complete.Guide.to.TensorFlow.for.Deep.Learning.with.Python.part1.rar http://nitroflare.com/view/E5FE35F0D42A645/htbpn.Complete.Guide.to.TensorFlow.for.Deep.Learning.with.Python.part2.rar http://nitroflare.com/view/6F39106E2D5C126/htbpn.Complete.Guide.to.TensorFlow.for.Deep.Learning.with.Python.part3.rar rapidgator_net: https://rapidgator.net/file/9e1dfe4f2a248620cfe8b9fdbec67da2/htbpn.Complete.Guide.to.TensorFlow.for.Deep.Learning.with.Python.part1.rar.html https://rapidgator.net/file/2e998bc51b7a71e4b6ba7f147df8c267/htbpn.Complete.Guide.to.TensorFlow.for.Deep.Learning.with.Python.part2.rar.html https://rapidgator.net/file/0645d64bc1f5873e2e649fdb7fb34e3c/htbpn.Complete.Guide.to.TensorFlow.for.Deep.Learning.with.Python.part3.rar.html
Links are Interchangeable - No Password - Single Extraction