What an thrilling time. It has been almost 4 years since Tensorflow was launched, and the library has developed to its official second model. Format File: [122 MP4] File Dimension: 6.96 GB
Tensorflow 2.0 Deep Learning and Artificial Intelligence
What you will study
Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
Predict Inventory Returns
Time Collection Forecasting
Pc Imaginative and prescient
The right way to construct a Deep Reinforcement Learning Inventory Buying and selling Bot
GANs (Generative Adversarial Networks)
Recommender Techniques
Picture Recognition
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Use Tensorflow Serving to serve your mannequin utilizing a RESTful API
Use Tensorflow Lite to export your mannequin for cell (Android, iOS) and embedded units
Use Tensorflow’s Distribution Methods to parallelize studying
Low-level Tensorflow, gradient tape, and construct your personal customized fashions
Pure Language Processing (NLP) with Deep Learning
Reveal Moore’s Regulation utilizing Code
Switch Learning to create state-of-the-art picture classifiers
Get instantly obtain Tensorflow 2.0 Deep Learning and Artificial Intelligence
Course content material
Broaden all 126 lectures20:48:08
–Welcome
22:26
Introduction
Preview
04:03
Define
12:47
The place to get the code
05:36
+Google Colab
4 lectures41:01
+Machine Learning and Neurons
10 lectures01:32:06
+Feedforward Artificial Neural Networks
9 lectures01:36:21
+Convolutional Neural Networks
11 lectures01:57:05
+Recurrent Neural Networks, Time Collection, and Sequence Information
18 lectures03:12:29
+Pure Language Processing (NLP)
6 lectures54:35
+Recommender Techniques
2 lectures22:27
+Switch Learning for Pc Imaginative and prescient
6 lectures44:48
+GANs (Generative Adversarial Networks)
2 lectures28:01
9 extra sections
Necessities
Know code in Python and Numpy
For the theoretical elements (non-obligatory), perceive derivatives and chance
Description
Welcome to Tensorflow 2.0!
What an thrilling time. It has been almost 4 years since Tensorflow was launched, and the library has developed to its official second model.
Tensorflow is Google’s library for deep studying and synthetic intelligence.
Deep Learning has been chargeable for some wonderful achievements lately, corresponding to:
Producing lovely, photo-realistic photographs of individuals and issues that by no means existed (GANs)
Beating world champions within the technique sport Go, and advanced video video games like CS:GO and Dota 2 (Deep Reinforcement Learning)
Self-driving automobiles (Pc Imaginative and prescient)
Speech recognition (e.g. Siri) and machine translation (Pure Language Processing)
Even creating movies of individuals doing and saying issues they by no means did (DeepFakes – a probably nefarious software of deep studying)
Tensorflow is the world’s hottest library for deep studying, and it is constructed by Google, whose dad or mum Alphabet lately grew to become essentially the most cash-rich firm on the earth (only a few days earlier than I wrote this). It’s the library of selection for a lot of corporations doing AI and machine studying.
In different phrases, if you wish to do deep studying, you gotta know Tensorflow.
This course is for beginner-level college students all the best way as much as expert-level college students. How can this be?
For those who’ve simply taken my free Numpy prerequisite, then all the things it is advisable leap proper in. We’ll begin with some very fundamental machine studying fashions and advance to state-of-the-art ideas.
Alongside the best way, you’ll find out about all the main deep studying architectures, corresponding to Deep Neural Networks, Convolutional Neural Networks (picture processing), and Recurrent Neural Networks (sequence knowledge).
Present initiatives embrace:
Pure Language Processing (NLP)
Recommender Techniques
Switch Learning for Pc Imaginative and prescient
Generative Adversarial Networks (GANs)
Deep Reinforcement Learning Inventory Buying and selling Bot
Get instantly obtain Tensorflow 2.0 Deep Learning and Artificial Intelligence
Even should you’ve taken all of my earlier programs already, you’ll nonetheless find out about convert your earlier code in order that it makes use of Tensorflow 2.0, and there are all-new and never-before-seen initiatives on this course corresponding to time sequence forecasting and do inventory predictions.
This course is designed for college kids who wish to study quick, however there are additionally “in-depth” sections in case you wish to dig slightly deeper into the idea (like what’s a loss operate, and what are the various kinds of gradient descent approaches).
Superior Tensorflow matters embrace:
Deploying a mannequin with Tensorflow Serving (Tensorflow within the cloud)
Deploying a mannequin with Tensorflow Lite (cell and embedded functions)
Distributed Tensorflow coaching with Distribution Methods
Writing your personal customized Tensorflow mannequin
Changing Tensorflow 1.x code to Tensorflow 2.0
Constants, Variables, and Tensors
Keen execution
Gradient tape
Teacher’s Observe: This course focuses on breadth reasonably than depth, with much less concept in favor of constructing extra cool stuff. If you’re on the lookout for a extra theory-dense course, this isn’t it. Typically, for every of those matters (recommender techniques, pure language processing, reinforcement studying, pc imaginative and prescient, GANs, and many others.) I have already got programs singularly targeted on these matters.
Thanks for studying, and I’ll see you at school!
Who this course is for:
Freshmen to superior college students who wish to find out about deep studying and AI in Tensorflow 2.0
