Automating Comic Book Creation with CrewAI Agents: Creative Content Generation
11:34
Automating Comic Book Creation with CrewAI Agents: Creative Content Generation
RAG Systems with Vision Language Models: Chatting with Complex Documents
11:06
RAG Systems with Vision Language Models: Chatting with Complex Documents
Collaborative AI Agent Framework for Automated EDA using CrewAI
21:57
Collaborative AI Agent Framework for Automated EDA using CrewAI
Fine-tuning OpenAI models
23:19
Fine-tuning OpenAI models
Q&A Generation with Self Evaluation - CrewAI Agents
14:09
Q&A Generation with Self Evaluation - CrewAI Agents
Harnessing LLMs for Automated Timeline Generation
9:48
Harnessing LLMs for Automated Timeline Generation
LLM Applications: Summarizng a document with key topics
21:58
LLM Applications: Summarizng a document with key topics
Applications of GenAI: Q&A Generation
13:02
Applications of GenAI: Q&A Generation
Story Telling: ChatGPT as Election Analyst
13:30
Story Telling: ChatGPT as Election Analyst
Introduction to Deep Learning
2:01:45
Introduction to Deep Learning
Session 15: Overfitting Vs. Underfitting
22:48
Session 15: Overfitting Vs. Underfitting
Querying EV Report using LLM
19:38
Querying EV Report using LLM
Session 14: Decision Trees for Classification
1:00:34
Session 14: Decision Trees for Classification
Analyzing Stock Performance using LLM
19:52
Analyzing Stock Performance using LLM
Session 13: Evaluation of Classification Models
1:12:59
Session 13: Evaluation of Classification Models
Story Telling using LLMs and Prompts
26:21
Story Telling using LLMs and Prompts
Session 12: Classification - Logistic Regression
56:01
Session 12: Classification - Logistic Regression
Exploratory Data Analysis Using LLM and LangChain
37:41
Exploratory Data Analysis Using LLM and LangChain
Session 11: Model Deployment
21:08
Session 11: Model Deployment
Session 10.2: Finding Neighbors - Deep Dive
16:39
Session 10.2: Finding Neighbors - Deep Dive
Session 10: K-Fold Cross Validation and Hyper-parameter Tuning
40:55
Session 10: K-Fold Cross Validation and Hyper-parameter Tuning
Session 9: Regression Using KNN
1:02:44
Session 9: Regression Using KNN
Session 8.1: Creating ML Pipeline
22:48
Session 8.1: Creating ML Pipeline
Session 7.3: Saving and Deploying a Model
19:18
Session 7.3: Saving and Deploying a Model
Session 7.1: Error Analysis - Regression
28:28
Session 7.1: Error Analysis - Regression
Session 7: Multiple Linear Regression
59:57
Session 7: Multiple Linear Regression
Session 6: ML Overview and Regression
1:28:46
Session 6: ML Overview and Regression
Session 5: Exploratory Data Analysis 2
1:26:43
Session 5: Exploratory Data Analysis 2
Session 4: Exploratory Data Analysis - 1
1:40:08
Session 4: Exploratory Data Analysis - 1
Session 3: Sampling Distribution and Hypothesis Test
1:34:29
Session 3: Sampling Distribution and Hypothesis Test