π Master Machine Learning in 60 Hours: Complete Python Course for Beginners & Beyond
Dive into this comprehensive 60-hour Machine Learning course with Python! Perfect for beginners and enthusiasts, this tutorial covers everything you need to build real-world AI solutions. Start your ML journey today!

Siddhardhan
665.4K views β’ Sep 5, 2022

About this video
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.
Complete Generative AI Course for Beginners: https://linktr.ee/siddhardhan
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
All presentation files for the Machine Learning course as PDF for as low as βΉ200 (INR): Drop a mail to siddhardhans2317@gmail.com
Github repository link for Colab Notebooks: https://github.com/siddhardhan23/Complete-Machine-Learning-Course-Part-1
All Datasets Link: https://drive.google.com/drive/folders/1NEs0rpFelfzSWAJ6y832EDpW9ImQH4QJ?usp=sharing
Timestamp for the topics covered in this Machine Learning Course video:
00:00 Introduction
4:22 AI vs ML vs DL
9:40 Types of Machine Learning
16:05 Supervised Learning & its Types
21:34 Unsupervised Learning & its Types
27:55 Deep Learning
36:11 Google Colaboratory - basics
45:53 Python Basics
1:08:36 Basic Data types in Python
1:28:40 List, Tuple, Set, Dictionary
1:55:36 Operators in Python
2:14:50 If Else Statement in Python
2:28:42 Loops in Python
2:44:20 Functions in Python
2:59:16 Numpy Tutorial
3:44:03 Pandas Tutorial
4:33:06 Matplotlib Tutorial
5:01:25 Seaborn Tutorial
5:37:34 Data Collection for ML
5:50:46 Importing datasets through Kaggle API
6:05:15 Handling Missing Values
6:29:58 Data Standardization
6:49:30 Label Encoding
7:06:56 Train Test Split
7:19:16 Handling Imbalanced Dataset
7:38:24 Feature Extraction of Text data
7:52:03 Numerical dataset processing
8:11:42 Textual data Processing
8:47:12 ML Use case 1: Rock vs Mine Prediction
9:35:35 ML Use case 2: Diabetes Prediction
10:38:53 ML Use case 3: Spam Mail Prediction
Machine Learning Projects Playlist: https://youtube.com/playlist?list=PLfFghEzKVmjvuSA67LszN1dZ-Dd_pkus6
Hello everyone! I am setting up a donation campaign for my YouTube Channel. If you like my videos and wish to support me financially, you can donate through the following means:
From India π UPI ID : siddhardhselvam2317@oksbi
Outside of India? π Paypal id: siddhardhselvam2317@gmail.com
(No donation is small. Every penny counts)
Thanks in advance!
LinkedIn: https://www.linkedin.com/in/siddhardhan-s-741652207
Telegram Group: https://t.me/siddhardhan
Facebook group: https://www.facebook.com/groups/490857825649006/?ref=share Instagram: https://www.instagram.com/siddhardhan23
Complete Generative AI Course for Beginners: https://linktr.ee/siddhardhan
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
All presentation files for the Machine Learning course as PDF for as low as βΉ200 (INR): Drop a mail to siddhardhans2317@gmail.com
Github repository link for Colab Notebooks: https://github.com/siddhardhan23/Complete-Machine-Learning-Course-Part-1
All Datasets Link: https://drive.google.com/drive/folders/1NEs0rpFelfzSWAJ6y832EDpW9ImQH4QJ?usp=sharing
Timestamp for the topics covered in this Machine Learning Course video:
00:00 Introduction
4:22 AI vs ML vs DL
9:40 Types of Machine Learning
16:05 Supervised Learning & its Types
21:34 Unsupervised Learning & its Types
27:55 Deep Learning
36:11 Google Colaboratory - basics
45:53 Python Basics
1:08:36 Basic Data types in Python
1:28:40 List, Tuple, Set, Dictionary
1:55:36 Operators in Python
2:14:50 If Else Statement in Python
2:28:42 Loops in Python
2:44:20 Functions in Python
2:59:16 Numpy Tutorial
3:44:03 Pandas Tutorial
4:33:06 Matplotlib Tutorial
5:01:25 Seaborn Tutorial
5:37:34 Data Collection for ML
5:50:46 Importing datasets through Kaggle API
6:05:15 Handling Missing Values
6:29:58 Data Standardization
6:49:30 Label Encoding
7:06:56 Train Test Split
7:19:16 Handling Imbalanced Dataset
7:38:24 Feature Extraction of Text data
7:52:03 Numerical dataset processing
8:11:42 Textual data Processing
8:47:12 ML Use case 1: Rock vs Mine Prediction
9:35:35 ML Use case 2: Diabetes Prediction
10:38:53 ML Use case 3: Spam Mail Prediction
Machine Learning Projects Playlist: https://youtube.com/playlist?list=PLfFghEzKVmjvuSA67LszN1dZ-Dd_pkus6
Hello everyone! I am setting up a donation campaign for my YouTube Channel. If you like my videos and wish to support me financially, you can donate through the following means:
From India π UPI ID : siddhardhselvam2317@oksbi
Outside of India? π Paypal id: siddhardhselvam2317@gmail.com
(No donation is small. Every penny counts)
Thanks in advance!
LinkedIn: https://www.linkedin.com/in/siddhardhan-s-741652207
Telegram Group: https://t.me/siddhardhan
Facebook group: https://www.facebook.com/groups/490857825649006/?ref=share Instagram: https://www.instagram.com/siddhardhan23
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Video Information
Views
665.4K
Likes
13.1K
Duration
11:35:42
Published
Sep 5, 2022
User Reviews
4.8
(133)