TensorFlow Full Course | Learn TensorFlow in 3 Hours | TensorFlow Tutorial For Beginners | Edureka

This Edureka TensorFlow Full Course video is a complete guide to Deep Learning using TensorFlow. It covers in-depth knowledge about Deep Learning, Tensorflow & Neural Networks. Below are the topics covered in this TensorFlow tutorial for beginners:
00:00 Introduction
2:07 Artificial Intelligence
2:21 Why Artificial Intelligence?
5:27 What is Artificial Intelligence?
5:55 Artificial Intelligence Domains
6:14 Artificial Intelligence Subsets
11:17 Machine Learning
12:32 Types of Machine Learning
12:39 Machine Learning Use Case
15:55 Supervised Learning
18:50 Types of Supervised Learning
20:17 Use Case 2
21:28 Linear Regression
26:34 Linear Regression Demo
38:39 Regression Application
40:14 Building Logistic Regression Model
40:24 Logistic Regression Use Case
46:55 Analysing Performance Of The Model
49:40 Calculating The Accuracy
51:31 Logistic Regression Demo
1:01:38 Clustering Use Case
1:05:12 How Clustering works?
1:05:12 Initialization
1:06:07 Cluster Assignment
1:07:37 Move Centroid
1:08:27 Optimization
1:08:32 Convergence
1:09:22 How to find optimal solution?
1:09:30 Choosing the number of cluster
1:16:35 Reinforcement Learning
1:17:35 Limitation of Machine Learning
1:22:00 How Deep Learning Solves the Issue?
1:25:05 What is Deep Learning?
1:26:35 Applications of Deep Learning
1:29:14 What is a Tensor?
1:29:48 Rank of Tensors
1:32:13 Shape of a Tensor
1:33:58 What is TensorFlow?
1:35:38 TensorFlow Code Basics
1:36:09 TensorFlow Basic Demo
2:00:33 Activation or Transformation Function
2:01:28 Linear
2:02:18 Unit Step
2:03:23 Sigmoid
2:04:23 Tanh
2:05:18 ReLU
2:05:53 Softmax
2:07:03 Activation Function Demo
2:10:43 How Neuron Works?
2:13:08 What is a Perceptron?
2:15:53 Role of Weights & Bias
2:16:18 Perceptron Example
2:22:23 Training a Perceptron
2:22:48 Perceptron Learning Algorithm
2:26:08 Training Network Weights
2:39:43 Reducing The Loss
2:43:18 Perceptron Learning Algorithm Demo

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#edureka #edurekaTensorFlow #TensorFlowTutorial #TensorFlowTutorialForBeginners #TensorFlowCompleteCourse

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How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course

Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.

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Who should go for this course?

The following professionals can go for this course:
1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. Business Analysts who want to understand Deep Learning (ML) Techniques
4. Information Architects who want to gain expertise in Predictive Analytics
5. Professionals who want to captivate and analyze Big Data
6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

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[monikasingh]

Thanks for this video. concepts are explained in the simplest possible way.

[shailavijay]

Its a very good seesion for begineer, Thanks edurekha

[tapanjeetroy]

Thanks a lot sir.. You have done a great job

[prabindahal]

Thankyou for so much of valuable videos.You guys are just awesome!

[DevMaster]

What an amazing tutorial @edureka team

[manojbajgain]

Omg why i am so late on this channel man... This channel is full of valuable treasures

[rafaelperez]

What a great tutorial, ! I'ver rarely seen complex concepts so well explained. Thanks a lot!

[Starman]

Plz do make a video for tensor flow installation

[Ankaia]

Wow I think this video will help a lot ! But is it with tensforflow or tensorflow 2.0 ?

[amritajena]

The best Tensor Flow Tutorial on YouTube, The flow of teaching by Amit is marvelous. Thank you Edureka. Will you please kindly provide the Jupyter notebook used in the session for reference. It will be of great help.

Hello I am watching right right(2:33:33) and you are using tensorflow 1.x Why don't you introduce 2.x. I could not find GradientDescentOptimizer function in tensorflow 2.x
Gradient descent applies much more differently in tf 2.x

[AmitSingh-zgkb]

Nice Content Delivery with good explanation sir 🙏🙏🙏💖💖💖

[yousfoss]

thks very much. what about the tensor graphical representation and decomposition

[yilunliu]

This is the best TensowFlow Tutorial i can find on YouTube, i have watched many others and feel it's too late to find this one. Thanks @edureka! Could anyone share the Jupyter notebook used in the lecture?