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This Edureka video on "Artificial Intelligence Full Course" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with handson examples. The following topics are covered in this Artificial Intelligence Full Course:

00:00 Introduction to Artificial Intelligence Course
02:27 History Of AI
06:45 Demand For AI
08:46 What Is Artificial Intelligence?
09:50 AI Applications
16:49 Types Of AI
20:24 Programming Languages For AI
27:12 Introduction To Machine Learning
28:08 Need For Machine Learning
31:48 What Is Machine Learning?
34:13 Machine Learning Definitions
37:26 Machine Learning Process
49:13 Types Of Machine Learning
49:21 Supervised Learning
52:00 Unsupervised Learning
53:44 Reinforcement Learning
55:29 Supervised vs Unsupervised vs Reinforcement Learning
58:23 Types Of Problems Solved Using Machine Learning
1:04:49 Supervised Learning Algorithms
1:05:17 Linear Regression
1:11:20 Linear Regression Demo
1:26:36 Logistic Regression
1:35:36 Decision Tree
1:55:18 Random Forest
2:07:31 Naive Bayes
2:14:37 K Nearest Neighbour (KNN)
2:20:31 Support Vector Machine (SVM)
2:26:40 Demo (Classification Algorithms)
2:42:36 Unsupervised Learning Algorithms
2:42:45 Kmeans Clustering
2:50:49 Demo (Unsupervised Learning)
2:56:40 Reinforcement Learning
3:24:36 Demo (Reinforcement Learning)
3:31:41 AI vs Machine Learning vs Deep Learning
3:33:08 Limitations Of Machine Learning
3:36:32 Introduction To Deep Learning
3:38:36 How Deep Learning Works?
3:40:48 What Is Deep Learning?
3:41:50 Deep Learning Use Case
3:43:14 Single Layer Perceptron
3:50:56 Multi Layer Perceptron (ANN)
3:52:55 Backpropagation
3:54:39 Training A Neural Network
4:01:02 Limitations Of Feed Forward Network
4:03:18 Recurrent Neural Networks
4:05:36 Convolutional Neural Networks
4:09:00 Demo (Deep Learning)
4:29:02 Natural Language Processing
4:30:53 What Is Text Mining?
4:32:43 What Is NLP?
4:33:26 Applications Of NLP
4:35:53 Terminologies In NLP
4:41:19 NLP Demo
4:47:21 Machine Learning Masters Program

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About the Masters Program

Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.

The Master's Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markov’s Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods.



Please write back to us at [email protected] or call us at IND: 9606058406 / US: +18338555775 (tollfree) for more information