AD-TEAM
3.38 GB | 20min 21s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 Section Intro.mp4 (36.9 MB)
2 Traditional Programming vs Machine Learning.mp4 (131.2 MB)
3 Supervised Learning.mp4 (76.57 MB)
4 Unsupervised Learning.mp4 (76.62 MB)
5 Reinforcement Learning.mp4 (74.77 MB)
6 Feature Engineering and Dataset Splitting.mp4 (53.89 MB)
7 Training vs Inference.mp4 (33.36 MB)
8 How fit is your Model Evaluation and OverUnderfitting.mp4 (47.33 MB)
9 Hyperparameter Tuning and Balancing BiasVariance.mp4 (58.48 MB)
10 Section Intro.mp4 (16.37 MB)
11 Linear Regression.mp4 (50.28 MB)
12 Logistic Regression.mp4 (26.63 MB)
13 Decision Tree.mp4 (28.24 MB)
14 Random Forest.mp4 (39.3 MB)
15 Support Vector Machines (SVMs).mp4 (25.29 MB)
16 Neural Networks.mp4 (45.23 MB)
17 Boosting Algorithms.mp4 (84.65 MB)
18 Module Summary.mp4 (29.69 MB)
19 Section Intro.mp4 (23.85 MB)
20 What and How of Large Language Models (LLMs).mp4 (47.58 MB)
21 Tokens and Parameters.mp4 (45.5 MB)
22 Transformers and Attention Mechanism.mp4 (46.98 MB)
23 Pre Training and Fine Tuning of Foundational Models.mp4 (35.54 MB)
24 Prompt Engineering.mp4 (69.38 MB)
25 Limitations of LLMs.mp4 (33.41 MB)
26 Retrieval Augmented Generation (RAG).mp4 (15.64 MB)
27 What is Agentic AI.mp4 (13.06 MB)
28 What is Agentic AI.mp4 (173.79 MB)
29 Goals and Tools.mp4 (82.04 MB)
30 Memory and Planning.mp4 (34.05 MB)
31 Agentic Architecture and Types of Agents.mp4 (100.51 MB)
32 Multi Agents, Examples and Challenges.mp4 (97.2 MB)
33 Agentic Devops, MLOps and Ethical Considerations.mp4 (43.2 MB)
34 Module Summary.mp4 (15.25 MB)
35 What is MLOps.mp4 (353.61 MB)
36 Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4 (308.49 MB)
37 Comparing Three Approach to AI – ML, LLM, Agentic.mp4 (351.02 MB)
38 MLOps Case Studies – Learning from the Pioneers.mp4 (123.96 MB)
39 Comparing Devops vs MLOps.mp4 (286.81 MB)
40 Emergence of a MLOps Engineer.mp4 (229.76 MB)]
Screenshot
1 Section Intro.mp4 (36.9 MB)
2 Traditional Programming vs Machine Learning.mp4 (131.2 MB)
3 Supervised Learning.mp4 (76.57 MB)
4 Unsupervised Learning.mp4 (76.62 MB)
5 Reinforcement Learning.mp4 (74.77 MB)
6 Feature Engineering and Dataset Splitting.mp4 (53.89 MB)
7 Training vs Inference.mp4 (33.36 MB)
8 How fit is your Model Evaluation and OverUnderfitting.mp4 (47.33 MB)
9 Hyperparameter Tuning and Balancing BiasVariance.mp4 (58.48 MB)
10 Section Intro.mp4 (16.37 MB)
11 Linear Regression.mp4 (50.28 MB)
12 Logistic Regression.mp4 (26.63 MB)
13 Decision Tree.mp4 (28.24 MB)
14 Random Forest.mp4 (39.3 MB)
15 Support Vector Machines (SVMs).mp4 (25.29 MB)
16 Neural Networks.mp4 (45.23 MB)
17 Boosting Algorithms.mp4 (84.65 MB)
18 Module Summary.mp4 (29.69 MB)
19 Section Intro.mp4 (23.85 MB)
20 What and How of Large Language Models (LLMs).mp4 (47.58 MB)
21 Tokens and Parameters.mp4 (45.5 MB)
22 Transformers and Attention Mechanism.mp4 (46.98 MB)
23 Pre Training and Fine Tuning of Foundational Models.mp4 (35.54 MB)
24 Prompt Engineering.mp4 (69.38 MB)
25 Limitations of LLMs.mp4 (33.41 MB)
26 Retrieval Augmented Generation (RAG).mp4 (15.64 MB)
27 What is Agentic AI.mp4 (13.06 MB)
28 What is Agentic AI.mp4 (173.79 MB)
29 Goals and Tools.mp4 (82.04 MB)
30 Memory and Planning.mp4 (34.05 MB)
31 Agentic Architecture and Types of Agents.mp4 (100.51 MB)
32 Multi Agents, Examples and Challenges.mp4 (97.2 MB)
33 Agentic Devops, MLOps and Ethical Considerations.mp4 (43.2 MB)
34 Module Summary.mp4 (15.25 MB)
35 What is MLOps.mp4 (353.61 MB)
36 Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4 (308.49 MB)
37 Comparing Three Approach to AI – ML, LLM, Agentic.mp4 (351.02 MB)
38 MLOps Case Studies – Learning from the Pioneers.mp4 (123.96 MB)
39 Comparing Devops vs MLOps.mp4 (286.81 MB)
40 Emergence of a MLOps Engineer.mp4 (229.76 MB)]
Screenshot
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