6.33 GB | 00:18:34 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 -RAG and Generative AI with Python Promotional Video (30.47 MB)
2 -Course Overview RAG and Generative AI with Python (110.78 MB)
3 -Diogo's Introduction and Background (54.18 MB)
4 -Unlimited Updates and Enhancements 2025 (27.05 MB)
1 -Game Plan for Fundamentals of Retrieval Systems (32.12 MB)
10 -Python - TF-IDF Function and Output Analysis (111.64 MB)
11 -Boolean Retrieval Model (30.51 MB)
12 -Python - Boolean Retrieval Implementation (238.5 MB)
13 -Probabilistic Retrieval Model (49.4 MB)
14 -Python - Probabilistic Retrieval Model (99.11 MB)
15 -How Google Search Works (94.76 MB)
16 -Key Concepts Indexing, Querying, and Ranking (58.19 MB)
17 -Section Recap Key Learnings (17.59 MB)
2 -Overview of Information Retrieval (40.52 MB)
3 -Understanding Tokenization in NLP (57.61 MB)
4 -Python - Libraries and Data Handling for RAG (56.09 MB)
5 -Python - Tokenization Techniques (75.08 MB)
6 -Python - Preprocessing Steps (131.8 MB)
7 -Types of Retrieval Systems (51.29 MB)
8 -Vector Space Model (TF-IDF) (54.05 MB)
9 -Python - Implementing TF-IDF (87.94 MB)
1 -Game Plan for Basics of Generation Models (12.91 MB)
10 -Python - Generating Text with GPT-2 (65.25 MB)
11 -Basics of Generation Models Recap Key Learnings (15.52 MB)
2 -Introduction to Text Generation (30.83 MB)
3 -Understanding Transformers (85.45 MB)
4 -Python - Text Generation with GPT-2 (177.95 MB)
5 -Python - Tokenization for Text Generation (92.04 MB)
6 -Python - Padding the Data for Consistency (73.38 MB)
7 -Attention Mechanisms in NLP (42.77 MB)
8 -Python - Creating a Dataset Class (129.17 MB)
9 -Python - Fine-Tuning the GPT-2 Model (130.59 MB)
1 -Game Plan for Integrating Retrieval and Generation (20.7 MB)
10 -Python - Configuring RAG with Parameters (89.19 MB)
11 -What Have We Learned and Where Do We Go from Here (26.59 MB)
12 -Would you help me (17.63 MB)
2 -Introduction to RAG Architecture (35.33 MB)
3 -Python - Tokenization and Embeddings for RAG (195.67 MB)
4 -FAISS Index Efficient Similarity Search (32.54 MB)
5 -Python - Building a Retrieval System (112.57 MB)
6 -Python - Developing a Generative Model (173.21 MB)
7 -Python - Implementing the RAG System (101.53 MB)
8 -Python - Defining a Relevant Context Distance (176.18 MB)
9 -Understanding Generation Model Parameters (39.16 MB)
1 -Game Plan for RAG with OpenAI Integration (33.61 MB)
10 -Python - Generating Embeddings (219.43 MB)
11 -Python - Building FAISS Index and Metadata Integration (107.44 MB)
12 -Python - Implementing a Robust Retrieval System (210.18 MB)
13 -Python - Combining Outputs for Enhanced Results (41.93 MB)
14 -Python - Constructing a Generative Model (170.72 MB)
15 -Python - Complete RAG System Implementation (100.62 MB)
16 -How to Improve RAG Systems Effectively (70.43 MB)
2 -Case Study Briefing Analyzing Cooking Books (39.55 MB)
3 -Python - Setting Up OpenAI API Key (81.42 MB)
4 -Python - Converting PDF to Images (128.74 MB)
5 -Python - Reading a Single Image with GPT (176.91 MB)
6 -Python - Enhancing AI with Prompt Engineering (143.66 MB)
7 -Python - Reading All Images in a Dataset (73.12 MB)
8 -Python - Filtering Non-relevant Information (103.15 MB)
9 -Understanding Embeddings in NLP (55.63 MB)
1 -Game Plan for Handling Unstructured Data (31.62 MB)
10 -Python - Setting Up Word Documents for RAG (92.21 MB)
11 -Python - Implementing RAG for Word Documents (35.7 MB)
12 -Working with PowerPoint Presentations (33.35 MB)
13 -Python - PowerPoint Setup for RAG (60.8 MB)
14 -Python - RAG Implementation for PowerPoint (49.75 MB)
15 -Working with Files (32.51 MB)
16 -Python - Setup for RAG (66.56 MB)
17 -Python - RAG Implementation for Files (29.42 MB)
18 -Working with PDF Files (32.91 MB)
19 -Python - PDF Setup for RAG (86.24 MB)
2 -Introduction to Langchain Library (56.62 MB)
20 -Python - RAG Implementation for PDF Files (91.55 MB)
21 -RAG with Unstructured Data Recap Key Learnings (32.72 MB)
3 -Excel Data Best Practices for Data Handling (42.05 MB)
4 -Python - Initial Setup for Data Processing (84.44 MB)
5 -Python - Loading Data and Implementing Chunking Strategies (79.99 MB)
6 -Python - Developing a Retrieval System for Unstructured Data (90.55 MB)
7 -Python - Building a Generation System for Dynamic Content (144.52 MB)
8 -Python - Building Retrieval and Generation Functions (135.81 MB)
9 -Working with Word Documents (35.4 MB)
2 -Course Overview RAG and Generative AI with Python (110.78 MB)
3 -Diogo's Introduction and Background (54.18 MB)
4 -Unlimited Updates and Enhancements 2025 (27.05 MB)
1 -Game Plan for Fundamentals of Retrieval Systems (32.12 MB)
10 -Python - TF-IDF Function and Output Analysis (111.64 MB)
11 -Boolean Retrieval Model (30.51 MB)
12 -Python - Boolean Retrieval Implementation (238.5 MB)
13 -Probabilistic Retrieval Model (49.4 MB)
14 -Python - Probabilistic Retrieval Model (99.11 MB)
15 -How Google Search Works (94.76 MB)
16 -Key Concepts Indexing, Querying, and Ranking (58.19 MB)
17 -Section Recap Key Learnings (17.59 MB)
2 -Overview of Information Retrieval (40.52 MB)
3 -Understanding Tokenization in NLP (57.61 MB)
4 -Python - Libraries and Data Handling for RAG (56.09 MB)
5 -Python - Tokenization Techniques (75.08 MB)
6 -Python - Preprocessing Steps (131.8 MB)
7 -Types of Retrieval Systems (51.29 MB)
8 -Vector Space Model (TF-IDF) (54.05 MB)
9 -Python - Implementing TF-IDF (87.94 MB)
1 -Game Plan for Basics of Generation Models (12.91 MB)
10 -Python - Generating Text with GPT-2 (65.25 MB)
11 -Basics of Generation Models Recap Key Learnings (15.52 MB)
2 -Introduction to Text Generation (30.83 MB)
3 -Understanding Transformers (85.45 MB)
4 -Python - Text Generation with GPT-2 (177.95 MB)
5 -Python - Tokenization for Text Generation (92.04 MB)
6 -Python - Padding the Data for Consistency (73.38 MB)
7 -Attention Mechanisms in NLP (42.77 MB)
8 -Python - Creating a Dataset Class (129.17 MB)
9 -Python - Fine-Tuning the GPT-2 Model (130.59 MB)
1 -Game Plan for Integrating Retrieval and Generation (20.7 MB)
10 -Python - Configuring RAG with Parameters (89.19 MB)
11 -What Have We Learned and Where Do We Go from Here (26.59 MB)
12 -Would you help me (17.63 MB)
2 -Introduction to RAG Architecture (35.33 MB)
3 -Python - Tokenization and Embeddings for RAG (195.67 MB)
4 -FAISS Index Efficient Similarity Search (32.54 MB)
5 -Python - Building a Retrieval System (112.57 MB)
6 -Python - Developing a Generative Model (173.21 MB)
7 -Python - Implementing the RAG System (101.53 MB)
8 -Python - Defining a Relevant Context Distance (176.18 MB)
9 -Understanding Generation Model Parameters (39.16 MB)
1 -Game Plan for RAG with OpenAI Integration (33.61 MB)
10 -Python - Generating Embeddings (219.43 MB)
11 -Python - Building FAISS Index and Metadata Integration (107.44 MB)
12 -Python - Implementing a Robust Retrieval System (210.18 MB)
13 -Python - Combining Outputs for Enhanced Results (41.93 MB)
14 -Python - Constructing a Generative Model (170.72 MB)
15 -Python - Complete RAG System Implementation (100.62 MB)
16 -How to Improve RAG Systems Effectively (70.43 MB)
2 -Case Study Briefing Analyzing Cooking Books (39.55 MB)
3 -Python - Setting Up OpenAI API Key (81.42 MB)
4 -Python - Converting PDF to Images (128.74 MB)
5 -Python - Reading a Single Image with GPT (176.91 MB)
6 -Python - Enhancing AI with Prompt Engineering (143.66 MB)
7 -Python - Reading All Images in a Dataset (73.12 MB)
8 -Python - Filtering Non-relevant Information (103.15 MB)
9 -Understanding Embeddings in NLP (55.63 MB)
1 -Game Plan for Handling Unstructured Data (31.62 MB)
10 -Python - Setting Up Word Documents for RAG (92.21 MB)
11 -Python - Implementing RAG for Word Documents (35.7 MB)
12 -Working with PowerPoint Presentations (33.35 MB)
13 -Python - PowerPoint Setup for RAG (60.8 MB)
14 -Python - RAG Implementation for PowerPoint (49.75 MB)
15 -Working with Files (32.51 MB)
16 -Python - Setup for RAG (66.56 MB)
17 -Python - RAG Implementation for Files (29.42 MB)
18 -Working with PDF Files (32.91 MB)
19 -Python - PDF Setup for RAG (86.24 MB)
2 -Introduction to Langchain Library (56.62 MB)
20 -Python - RAG Implementation for PDF Files (91.55 MB)
21 -RAG with Unstructured Data Recap Key Learnings (32.72 MB)
3 -Excel Data Best Practices for Data Handling (42.05 MB)
4 -Python - Initial Setup for Data Processing (84.44 MB)
5 -Python - Loading Data and Implementing Chunking Strategies (79.99 MB)
6 -Python - Developing a Retrieval System for Unstructured Data (90.55 MB)
7 -Python - Building a Generation System for Dynamic Content (144.52 MB)
8 -Python - Building Retrieval and Generation Functions (135.81 MB)
9 -Working with Word Documents (35.4 MB)
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