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Build Machine Learning Models and Neural Networks
Machine Learning: Beginners - Build Beginner Models in TensorFlow 2.0
01 Course Overview-1 (3:30)
02 Build Models On The Web-2 (5:06)
Source Files
02 AI Uninformed Search Algorithms
01 What Are Search Algorithms-1 (7:21)
02 Depth First Search-2 (9:00)
02b Build A Depth First Search Algorithm-3 (8:26)
03 What Is Breadth First Search (bfs)-4 (5:08)
03b Build A Breadth First Search Algorithm-5 (6:56)
04 Depth Limited Search-6 (3:58)
05 Iterative Deepening Depth First Search-7 (5:32)
06 What Is Uniform Cost Search-8 (6:04)
06b Build A Uniform Cost Search Algorithm-9 (8:07)
07 Bidirectional Search-10 (4:44)
Source Files
03 AI Informed Search Algorithms
01 What Are Informed Search Algorithms-1 (4:07)
02 What Is Greedy Best-first Search-2 (8:16)
02b Build A Greedy Best First Search Algorithm-3 (10:43)
03 What Is A Search-4 (5:10)
Source Files
04 How Machine Learning Works
01 How Does A Machine Learning Agent Learn-1 (7:37)
02 What Is Inductive Learning-2 (4:10)
03 Make Decisions With Decision Trees-3 (10:50)
04 Performance Of A Machine Learning Algorithm-4 (4:13)
05 Handle Noise In Data-5 (5:20)
06 Statistical Learning-6 (3:56)
Source Files
05 Logistic Regression
05 Source Files
05.01 What Is Logistic Regression-1 (4:26)
05.03 Prepare Data For Logistic Regression-2 (12:19)
05.03a How To Prepare Data-3 (8:52)
05.04 Build A Logistic Regression Model-4 (5:29)
05.04a How To Build A Logistic Regression Model-5 (3:28)
05.04b What Is Optimization-6 (12:10)
05.05 Optimize The Logistic Regression Model-7 (12:44)
05.05a How To Optimize A Logistic Regression Model-8 (12:45)
05.06 Train The Model-9 (10:09)
05.07 Test The Model-10 (2:33)
05.08 Visualize Results-11 (5:38)
06 Gradient Boosted Classification
06.01 What Is Gradient Boosting-1 (1:54)
06.02 Prepare Data For Gradient Boosted Classification-2 (7:19)
06.03 Build Binary Classes-3 (6:12)
06.04a How To Shape Data For Classification-4 (2:58)
06.04b Shape Data For Classification-5 (7:06)
06.05a How To Build A Boosted Trees Classifier-6 (4:03)
06.05b Build A Boosted Trees Classifier-7 (4:37)
06 Source Files
07 Gradient Boosted Regression
07.01 Build Input Functions-1 (3:55)
07.02 Build A Boosted Trees Regressor-2 (3:02)
07.03 Train And Evaluate The Model-3 (4:07)
07 Source Files
05 Source Files
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