Krish Naik Courses

Introduction to Statistics in Data Science

Comprehensive introduction to key statistical concepts in data science, covering population, sampling, variables, measurement scales, and data visualization techniques.

• YouTube
• 1 hour 29 minutes
• Self-Paced
• Free Video

Face Matching Application Using Deep Learning - End to End Implementation

Develop a Bollywood celebrity face matching application using deep learning, covering data collection, architecture design, environment setup, implementation stages, and web app creation.

• YouTube
• 3 hours 16 minutes
• Self-Paced
• Free Video

Implementation of Perceptron in Deep Learning Using Python from Scratch

Comprehensive guide to implementing perceptrons in Python, covering theory and practical coding from scratch for deep learning enthusiasts and AI developers.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Deep Learning - All Optimizers in One Video - SGD with Momentum, Adagrad, Adadelta, RMSprop, Adam Optimizers

Comprehensive exploration of deep learning optimizers, covering gradient descent, SGD, momentum, Adagrad, Adadelta, RMSprop, and Adam, with detailed explanations and comparisons.

• YouTube
• 1 hour 42 minutes
• Self-Paced
• Free Video

Implementation of End to End Kaggle Machine Learning Project With Deployment

Comprehensive guide to implementing a machine learning project for car price prediction, covering data exploration, model fitting, and deployment on Heroku.

• YouTube
• 1 hour 31 minutes
• Self-Paced
• Free Video

End-to-End ML Project with Deployment - Project Structure, Logging, and Exception Handling - Tutorial 2

Learn to structure, log, and handle exceptions in an end-to-end machine learning project, focusing on practical implementation and deployment techniques.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

How to Deploy End to End ML Projects in Production AWS Cloud Using CI CD Pipeline

Deploy ML projects on AWS using CI/CD pipeline, ECR, and EC2. Learn to set up Docker, IAM, and App Runner for seamless end-to-end deployment of machine learning applications in the cloud.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

Docker for Data Science Tutorial

Comprehensive Docker tutorial for data scientists, covering containers, images, installation, and Docker Compose. Learn to implement end-to-end data science projects using Docker.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

End to End MLOPS Data Science Project Implementation With Deployment

Comprehensive MLOps project implementation covering data ingestion, validation, transformation, model training, and deployment on AWS EC2 using MLflow and GitHub Actions.

• YouTube
• 2 hours 33 minutes
• Self-Paced
• Free Video

Step-by-Step Machine Learning Project Implementation: EDA, Feature Engineering, Selection, and Model Training

Comprehensive guide to implementing a machine learning project, covering data cleaning, EDA, feature engineering, selection, model training, and hyperparameter tuning.

• YouTube
• 1 hour 26 minutes
• Self-Paced
• Free Video

End to End Deep Learning Project Using MLOPS DVC Pipeline With Deployments Azure and AWS - Krish Naik

Comprehensive guide to building and deploying a deep learning project for chicken disease classification using MLOps tools, DVC pipeline, and cloud platforms Azure and AWS.

• YouTube
• 3 hours 51 minutes
• Self-Paced
• Free Video

Machine Learning Series - Revising Complete Linear Regression, Cost Function, Convergence Algorithm

Comprehensive review of linear regression, covering simple and multiple regression, cost function, and convergence algorithms with mathematical intuition and practical examples.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

Anomaly Detection Tutorials - Machine Learning and Its Types With Implementation

Comprehensive tutorial on anomaly detection techniques in machine learning, covering Isolation Forest, DBSCAN clustering, and Local Outlier Factor with practical implementations and examples.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Inside ChatGPT- Unveiling the Training Process of OpenAI's Language Model

Explore the training process behind ChatGPT, including generative pretraining, supervised fine-tuning, and reinforcement learning through human feedback. Gain insights into AI language model development.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

End to End NLP Project Implementation With Deployment Github Action - Text Summarization - Krish Naik

Comprehensive guide to implementing an end-to-end NLP text summarization project, covering data processing, model training, evaluation, and deployment using GitHub Actions on AWS.

• YouTube
• 3 hours 38 minutes
• Self-Paced
• Free Video