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**AD-TEAM** · 11-06-2024, 05:31 PM

7.16 GB | 00:08:54 | mp4 | 1920X1080 | 16:9
Genre:eLearning |Language:English

Files Included :
1 - Install Ollama (18.06 MB)
10 - Ollama Model Commands show (112.57 MB)
11 - Ollama Model Commands set clear savemodel and loadmodel (151.99 MB)
12 - Ollama Raw API Requests (162.5 MB)
13 - Load Uncesored Models for Banned Content Generation Only Educational Purpose (131.33 MB)
2 - Touch Base with Ollama (73.99 MB)
3 - Inspecting LLAMA 32 Model (34.5 MB)
4 - LLAMA 32 Benchmarking Overview (16.03 MB)
5 - What Type of Models are Available on Ollama (68 MB)
6 - Ollama Commands ollama server ollama show (51.64 MB)
7 - Ollama Commands ollama pull ollama list ollama rm (38.11 MB)
8 - Ollama Commands ollama cp ollama run ollama ps ollama stop (67.8 MB)
9 - Create and Run Ollama Model with Predefined Settings (132.81 MB)
76 - Introduction to Unstructured Data Loader (100.6 MB)
77 - Load PPTX Data with DataLoader (88.88 MB)
78 - Process PPTX data for LLM (92.4 MB)
79 - Generate Speaker Script for Your PPTX Presentation (84.7 MB)
80 - Loading and Parsing Excel Data for LLM (25.14 MB)
81 - Ask Questions from LLM for given Excel Data (15.53 MB)
82 - Load DOCX Document and Write Personalized Job Email (59.07 MB)
83 - Load YouTube Video Subtitles (67.45 MB)
84 - Load YouTube Video Subtitles in 10 Mins Chunks (22.45 MB)
85 - Generate YouTube Keywords from the Transcripts (53.32 MB)
86 - Introduction to RAG Project (27.37 MB)
87 - Introduction to FAISS and Chroma Vector Database (36.25 MB)
88 - Load All PDF Documents (45.58 MB)
89 - Recursive Text Splitter to Create Documents Chunk (99.25 MB)
90 - How Important Chunk Size Selection is (62.31 MB)
91 - Get OllamaEmbeddings (47.48 MB)
92 - Document Indexing in Vector Database (32.43 MB)
93 - How to Save and Search Vector Database (23.92 MB)
94 - Load Vector Database for RAG (82.14 MB)
95 - Get Vector Store as Retriever (44.26 MB)
96 - Exploring Similarity Search Types with Retriever (83.79 MB)
97 - Design RAG Prompt Template (53.59 MB)
98 - Build LLM RAG Chain (49.57 MB)
99 - Prompt Tuning and Generate Response from RAG Chain (31.26 MB)
100 - What is Tool Calling (67.55 MB)
101 - Available Search Tools at Langchain (27.98 MB)
102 - Create Your Custom Tools (23.61 MB)
103 - Bind tools with LLM (31.4 MB)
104 - Working with Tavily and DuckDuckGo Search Tools (50.83 MB)
105 - Working with Wikipedia and PubMed Tools (69.32 MB)
106 - Creating Tool Functions for InBuilt Tools (35.64 MB)
107 - Calling Tools with LLM (21.48 MB)
108 - Passing Tool Calling Result to LLM Part 1 (43.92 MB)
109 - Passing Tool Calling Result to LLM Part 2 (86.2 MB)
110 - How Agent Works (27.72 MB)
111 - Tools Preparation for Agent (71.08 MB)
112 - More About the Agent Working Process (31.77 MB)
113 - Selection of Prompt for Agent (61.03 MB)
114 - Agent in Action (83.38 MB)
115 - Create MySQL Connection with Local Server (56.83 MB)
116 - Get MySQL Execution Chain (64.12 MB)
117 - Correct Malformed MySQL Queries Using LLM (67.79 MB)
118 - MySQL Query Chain Execution (33.09 MB)
119 - MySQL Query Execution with Agents in LangGraph (126.95 MB)
14 - Langchain Introduction (93.9 MB)
15 - Lanchain Installation (105.98 MB)
16 - Langsmith Setup of LLM Observability (84.84 MB)
17 - Calling Your First Langchain Ollama API (75.04 MB)
18 - Generating Uncensored Content in Langchain Educational Purpose (91.89 MB)
19 - Trace LLM Input Output at Langsmith (87.78 MB)
20 - Going a lot Deeper in the Langchain (135.35 MB)
21 - Why We Need Prompt Template (31.13 MB)
22 - Type of Messages Needed for LLM (47.86 MB)
23 - Circle Back to ChatOllama (84.3 MB)
24 - Use Langchain Message Types with ChatOllama (80.41 MB)
25 - Langchain Prompt Templates (105.49 MB)
26 - Prompt Templates with ChatOllama (118.91 MB)
27 - Introduction to LCEL (72.65 MB)
28 - Create Your First LCEL Chain (106.24 MB)
29 - Adding StrOutputParser with Your Chain (115.16 MB)
30 - Chaining Runnables Chain Multiple Runnables (39.3 MB)
31 - Run Chains in Parallel Part 1 (76.49 MB)
32 - Run Chains in Parallel Part 2 (62.11 MB)
33 - How Chain Router Works (39.11 MB)
34 - Creating Independent Chains for Positive and Negative Reviews (37.75 MB)
35 - Route Your Answer Generation to Correct Chain (49.17 MB)
36 - What is RunnableLambda and RunnablePassthrough (33.7 MB)
37 - Make Your Custom Runnable Chain (53.32 MB)
38 - Create Custom Chain with chain Decorator (19.53 MB)
39 - What is Output Parsing (66.04 MB)
40 - What is Pydantic Parser (51.83 MB)
41 - Get Pydantic Parser Instruction (55.3 MB)
42 - Parse LLM Output Using Pydantic Parser (63.37 MB)
43 - Parsing with withstructuredoutput method (34.44 MB)
44 - JSON Output Parser (17.81 MB)
45 - CSV Output Parsing CommaSeparatedListOutputParser (28.39 MB)
46 - Datetime Output Parsing (41.62 MB)
47 - How to Save and Load Chat Message History Concept (75.5 MB)
48 - Simple Chain Setup (65.91 MB)
49 - Chat Message with History Part 1 (49.17 MB)
50 - Chat Message with History Part 2 (65.33 MB)
51 - Chat Message with History using MessagesPlaceholder (100.73 MB)
52 - Introduction (37.23 MB)
53 - Introduction To Streamlit and Our Chat Application (38.19 MB)
54 - Chat Bot Basic Code Setup (68.87 MB)
55 - Create Chat History in Streamlit Session State (48.71 MB)
56 - Create LLM Chat Input Area with Streamlit (71.97 MB)
57 - Update Historical Chat on Streamlit UI (50.88 MB)
58 - Complete Your Own Chat Bot Application (22.66 MB)
59 - Stream Output of Your Chat Bot like ChatGPT (33.84 MB)
60 - Introduction to PDF Document Loaders (86.61 MB)
61 - Load Single PDF Document with PyMuPDFLoader (67.06 MB)
62 - Load All PDFs from a Directory (64.46 MB)
63 - Combine All PDFs Data as Context Text (50.26 MB)
64 - How Many Tokens are There in Contex Data (42.96 MB)
65 - Make Question Answer Prompt Templates and Chain (31.02 MB)
66 - Ask Questions from Your PDF Documents (63.07 MB)
67 - Summarize Your PDF Documents (40.72 MB)
68 - Project 3 Generate Detailed Structured Report from the PDF Documents (66.21 MB)
69 - Introduction to Webpage Loaders (94.53 MB)
70 - Load Unstructured Stock Market Data (46.07 MB)
71 - Make LLM QnA Script (27.44 MB)
72 - Catastrophic Forgetting of LLM (22.92 MB)
73 - Break Down Large Text Data Into Chunks (42.48 MB)
74 - Create Stock Market News Summary for Each Chunks (94.53 MB)
75 - Generate Final Stock Market Report (82.87 MB)

Screenshot
[Image: fwBtZEj7_o.jpg]