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This Edureka video on “Synthetic Intelligence” will offer you a complete and detailed information of Synthetic Intelligence ideas with hands-on examples.

Following matters are lined on this video:
00:00 Introduction
02:27 Historical past Of AI
06:45 Demand For AI
08:46 What Is Synthetic Intelligence?
09:50 AI Functions
16:49 Sorts Of AI
20:24 Programming Languages For AI
27:12 Introduction To Machine Studying
28:08 Want For Machine Studying
31:48 What Is Machine Studying?
34:13 Machine Studying Definitions
37:26 Machine Studying Course of
49:13 Sorts Of Machine Studying
49:21 Supervised Studying
52:00 Unsupervised Studying
53:44 Reinforcement Studying
55:29 Supervised vs Unsupervised vs Reinforcement Studying
58:23 Sorts Of Issues Solved Utilizing Machine Studying
1:04:49 Supervised Studying Algorithms
1:05:17 Linear Regression
1:11:20 Linear Regression Demo
1:26:36 Logistic Regression
1:35:36 Choice Tree
1:55:18 Random Forest
2:07:31 Naive Bayes
2:14:37 Okay Nearest Neighbour (KNN)
2:20:31 Help Vector Machine (SVM)
2:26:40 Demo (Classification Algorithms)
2:42:36 Unsupervised Studying Algorithms
2:42:45 Okay-means Clustering
2:50:49 Demo (Unsupervised Studying)
2:56:40 Reinforcement Studying
3:24:36 Demo (Reinforcement Studying)
3:31:41 AI vs Machine Studying vs Deep Studying
3:33:08 Limitations Of Machine Studying
3:36:32 Introduction To Deep Studying
3:38:36 How Deep Studying Works?
3:40:48 What Is Deep Studying?
3:41:50 Deep Studying Use Case
3:43:14 Single Layer Perceptron
3:50:56 Multi Layer Perceptron (ANN)
3:52:55 Backpropagation
3:54:39 Coaching A Neural Community
4:01:02 Limitations Of Feed Ahead Community
4:03:18 Recurrent Neural Networks
4:05:36 Convolutional Neural Networks
4:09:00 Demo (Deep Studying)
4:29:02 Pure Language Processing
4:30:53 What Is Textual content Mining?
4:32:43 What Is NLP?
4:33:26 Functions Of NLP
4:35:53 Terminologies In NLP
4:41:19 NLP Demo
4:47:21 Machine Studying Masters Program

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Statistics and Likelihood Tutorial: https://www.youtube.com/watch?v=XcLO4f1i4Yo

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———–𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐔𝐧𝐢𝐯𝐞𝐫𝐬𝐢𝐭𝐲 𝐏𝐫𝐨𝐠𝐫𝐚𝐦———-

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Concerning the Masters Program

Edureka’s Machine Studying Engineer Masters Program makes you proficient in methods like Supervised Studying, Unsupervised Studying and Pure Language Processing. It contains coaching on the newest developments and technical approaches in Synthetic Intelligence & Machine Studying reminiscent of Deep Studying, Graphical Fashions and Reinforcement Studying.

The Grasp’s Program Covers Subjects LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Studying Methods and Synthetic Intelligence Sorts
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Circulate
Deep studying
Keras
Neural Networks
Bayesian and Markov’s Fashions
Inference
Choice Making
Bandit Algorithms
Bellman Equation
Coverage Gradient Strategies.

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