Complete Machine Learning Course in 60 Hours – Part 2 | Full Machine Learning Course for Beginners



Complete Generative AI Course for Beginners: https://www.udemy.com/course/generative-ai-for-beginners-chatbots-rag-mcp-ai-agents/?couponCode=DB168D66C47C2F715814 Hi! I will be conducting one-on-one discussion with all channel members. Checkout the perks and Join membership if interested: https://www.youtube.com/channel/UCG04dVOTmbRYPY1wvshBVDQ/join Check membership Perks: https://www.youtube.com/channel/UCG04dVOTmbRYPY1wvshBVDQ/join
. This Complete Machine Learning Course video will help you understand and learn Machine Learning in detail. This Machine Learning Tutorial is ideal for both beginners as well as professionals who want to master Machine Learning concepts & practice.

All presentation files for the Machine Learning course as PDF for as low as ₹200 (INR): Drop a mail to [email protected]

Complete Machine Learning Course in 60 Hours – Part 1: https://youtu.be/LcWFedjaR4Q

Github repository link for Colab Notebooks: https://github.com/siddhardhan23/Complete-Machine-Learning-Course-Part-2

All Datasets Link: https://drive.google.com/drive/folders/1RjK30edxWBlkK37w-9gY1JmmWFN4kUkO?usp=sharing

Timestamp for the topics covered in this Machine Learning Course video:

00:00 Introduction
5:15 Mathematics for ML – Introduction
10:39 Linear Algebra – Vectors
20:40 Vector Operations – Part 1
33:35 Vector Operations in Python – Part 1
53:18 Vector Operations – Part 2
1:03:34 Vector Operations in Python – Part 2
1:22:06 Matrix – Basics
1:35:45 Working with Matrix in Python
1:54:09 Matrix Operations
2:12:36 Matrix Operations in Python
2:44:38 Statistics for ML – Intro
2:53:26 Statistics Basics & Types of Data
3:06:55 Types of Statistics
3:20:46 Statistical Study – Types
3:32:57 Population & Sample
3:56:24 Central Tendencies
4:12:45 Measure of Variability
4:25:25 Percentiles & Quantiles
4:34:10 Correlation & Causation
4:47:41 Hypothesis Testing
4:57:45 Probability for ML
5:05:55 Basics of Probability
5:15:52 Random Variables & its Types
5:25:22 Probability Distribution for Random Variables
5:35:18 Normal Distribution & Skewness
5:44:55 Poisson Distribution
5:55:19 Module 6: ML Models
6:16:07 Supervised Learning Models
6:24:05 Unsupervised Learning Models
6:30:45 Model Selection & Cross Validation
6:45:01 Overfitting
6:59:03 Underfitting
7:07:37 Bias Variance Tradeoff
7:26:12 Loss Function
7:40:24 Model Evaluation
7:55:58 Model Parameters & Hyperparameters
8:28:15 Gradient Descent
8:54:01 ML Use Case 4: Heart Disease Prediction
10:32:55 ML Use Case 6: Loan Approval Prediction

Note: Audio is not proper for “ML Use Case 5: House Price Prediction”
Kindly check this video for House Price Prediction alone: https://youtu.be/fw5rkjq4Tfo

Machine Learning Projects Playlist: https://youtube.com/playlist?list=PLfFghEzKVmjvuSA67LszN1dZ-Dd_pkus6

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