42- Multiple Linear Regression and Machine Learning in Python-(Day-20)
Machine Learning helps you build models that can make predictions and take decisions of their own. This video on Types of Machine Learning and Algorithms will make you understand what Machine Learning is and the various types of Machine Learning.
This videos explains the Multiple Linear Regression for Machine Learning in Python.
The other types are in the next videos in the same playlist:
-Supervised Machine Learning and its algorithms
Logistic Regression.
K-Nearest Neighbors(K-NN)
Support Vector Machine(SVM)
Kernel SVM.
Naive Bayes
Decision Tree Classification.
Random Forest Classification
-unsupervised Machine Learning and its algorithms
K-Means Clustering
Hierarchical Clustering.
Probabilistic Clustering
-semisupervised Machine Learning and its algorithms
-Reinforcement Machine Learning and its algorithms
Model-Free Reinforcement Learning.
Policy Optimization.
Q-Learning
Model-Based Reinforcement Learning.
Learn the Model
Given the Model.
To join our course: https://t.me/+-WQcbjQGhsUyZjBk
This course revolves around the basic concepts of using Python for Data Science in Urdu and Hindi language. The target audience for this course in Pakistani National working in data Science or the beginners who want to learn this complete course via registration process. You can register any time with the following link: https://forms.gle/cS4KCZ6veQ1LtpFB8
only if you are interested in this 40 days long course (python_ka_chilla with baba_aammar.
More about me: I am Dr Aammar Tufail, your instructor in Python_ka_chilla. My aim is to train people in Data Science, machine learning, artificial intelligence, and deep learning by the end of the year (2022).
If you are keen to learn from this complete course, then here is the playlist for the course:
• Python_ka_chilla (python in 40 days in urd...
If you want to learn Data Science with R here is the completed and uploaded course in urdu, link:
• Complete Data Science Course in R
If you have any questions, you can always write in the comment section of the video, you have a question about.
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