IITKAIRefVid IIT KANPUR AI ML DL Course Reference Videos
Go back to Reference Page AI ML DL Course https://brahmavad.in/iitkairef/
Stanford CS229: Machine Learning Course, Lecture 1 – Andrew Ng (Autumn 2018)
https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
How To Learn Any Skill So Fast It Feels Illegal
Justin Sung
Mathematical Foundations for Machine Learning (Introduction Video)
Do THIS instead of watching endless tutorials – how I’d learn Python FAST…
Tech With Tim
Today we’re talking about learning Python efficiently, not the endless tutorial cycle that keeps you stuck, but an actual strategy that works. Tutorials are great, but we all know about “tutorial hell”, and even though that’s a majority of what I provide on this channel, I don’t want to see you get stuck there. Let’s quickly cover why Python is worth your time and then we’ll get into the strategy for learning it.
Do You Still Need to Learn Python in the Age of AI? MIT OpenCourseWare
Beginner AI Workshop: Learn & Code a Simple AI System
👉 AI basics: supervised vs. unsupervised learning, models, and algorithms
👉 How to build a collaborative filtering recommendation system using pandas and numpy
Supervised vs Unsupervised Learning – Machine Learning Explained!
We delve into the foundational concepts of supervised and unsupervised learning in machine learning. Learn how linear regression models the relationship between variables, explore the role of classification models, and understand the difference between supervised and unsupervised techniques. Whether you’re a data science beginner or looking to refresh your knowledge, this video provides a clear and comprehensive overview. Machine learning is the field of computer science that gives computer systems the ability to learn from data — and it’s one of the hottest topics in the industry right now. What You’ll Learn In This Video:
- Supervised Learning Techniques: Explore key methods like regression and classification. Understand how labeled data can be used to train models to predict outcomes and classify information.
- Unsupervised Learning Methods: Discover the power of clustering and other techniques that enable systems to identify patterns and group data without predefined labels.
- Conceptual Differences: Gain clarity on the essential differences between supervised and unsupervised learning, and learn how each approach can be applied to solve various real-world problems.
Introduction to Linear Regression – Machine Learning Explained!
We’ll explore the foundational concept of linear regression in machine learning. Learn how linear regression models the relationship between variables, understand how it finds the best fit straight line, and explore its application in solving real-world problems. Whether you’re a data science beginner or looking to deepen your knowledge, this video provides a clear and comprehensive overview. Machine learning is the field of computer science that gives computer systems the ability to learn from data — and it’s one of the hottest topics in the industry right now. What You’ll Learn In This Video:
- Linear Regression Fundamentals: Discover what linear regression is and how it models relationships in data.
- Best Fit Line: Understand how linear regression finds the best fit straight line to represent data relationships.
- Regression Applications: Gain insight into the practical applications of regression and the types of problems it solves.
Applications of Regression – Machine Learning in Action
In this video, we explore the real-world applications of regression in machine learning. Learn how this versatile and simple technique is widely used across industries to analyze trends, make predictions, and uncover insights in data. Whether you’re a beginner or looking to deepen your knowledge, this video offers a clear and practical overview. Machine learning is the field of computer science that allows computer systems to learn from data, and it’s one of the hottest topics in the industry right now. What You’ll Learn In This Video: Characteristics of Regression: Discover why regression is valued for its simplicity and adaptability. Real-World Use Cases: Explore applications of regression in fields such as finance, healthcare, and marketing. Predictive Power: Learn how regression techniques provide insights and predictions to solve various challenges.
Linear Regression, Clearly Explained!!!
The concepts behind linear regression, fitting a line to data with least squares and R-squared, are pretty darn simple, so let’s get down to it!
The Sigmoid Function Clearly Explained
5. Tanh Activation Function | ACTIVATION FUNCTION
Softmax Activation Function || Softmax Function || Quick Explained || Developers Hutt
SoftMax Activation Function in Neural Networks SoftMax function Solved example by Mahesh Huddar
ReLU (Rectified Linear Unit)
Neural Networks Pt. 3: ReLU In Action!!!
StatQuest with Josh Starmer
@statquest
Mastering ReLU & Leaky ReLU Activation Functions | Rectified Linear Unit (ReLU) |Hindi Tutorial
Activation Functions | Deep Learning Tutorial 8 (Tensorflow Tutorial, Keras & Python)
codebasics
One-hot Encoding explained deeplizard 161K subscribers
Quick explanation: One-hot encoding
Cross Entropy Udacity
Categorical Cross Entropy Explained | Beginner’s Guide | Loss functions DataMites
Categorical Cross Entropy | Artificial Neural Networks Gate Sma