Curriculum for this course
0 Lessons
00:00:00 Hours
Topics covered
- 1) Basics Of Machine Learning 2) Linear Regression 3) Logistic Regression 4) Decision Trees 5) Statistics & Distribution
- 6) Hypothesis testing 7) Supervised Learning 8) Unsupervised Learning 9) Reinforcement Learning 10) Probability and classification, Bayes optimal decisions
- 11) Naive Bayes and Gaussian class-conditional distribution . 11) Linear discriminant analysis 12) Principal Component Analysis 13) Learning Vector Quantization 14) Regularization methods:- Ridge,15) LASSO
- 16) K-Nearest Neighbors (KNN) 17) K means clustering 18) Dimensionality Reduction 19) Neural Networks
- 20) Concept of Agent in AI 21) Heuristic Search using Simple and Steepest hill climbing 23) Best First Search Algorithm 24) A* Algorithm
- 22) Apriori Algorithm (Association Rule) 23) Support Vector Machines
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Description
Lecture Schedule: starts 25th June
Two lectures a week for 8 consecutive weeks.
LIVE online Lectures Every Tuesday and Thursdays 7 pm to 9 pm
Introduction video
No videos available
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About the instructor
- 10 Reviews
- 395 Students
- 166 Courses
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Lead Instructor
Junkminds Team Comprises of highly qualified and skilled instructructors. Each topic is carefullychosen,analyzed and recorded for the maximum benefit of students.
Student feedback
Reviews
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Wed, 06-Jul-2022Abhishek NEGI
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