Jain Online LMS
Machine Learning
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Syllabus & Course Details
Syllabus
MODULE I : Introduction to Python and Introduction to Learning Expression and Arithmetic’s Learning
Video - Q Learning A Simplistic Application Applications of AI
Video - Introduction to Machine Learning Machine Learning Normal Computer Vs ML Machine Learning Algorithms Types of Machine Learning
Video - Types of Machine Learning Supervised Learning Process Overview Types of Supervised Learning
Video - Linear Regression
Video - Introduction to Python Introduction to Learning
Video - Supervised Learning
Video - Supervised Learning - Part2
Video - Linear Discriminants
Textual Notes
Unit I - Video
MODULE II : Linear Models
Video - Support Vector Machine
Video - Feedforward Neural Networks Artificial Neural Networks Perceptron Sigmoid neuron Activation Function The Learning Rate XOR
Video - Introduction to Linear Models Linear Relationship Reflection Question 1 Introduction Non - Linear Model Comparison
Video - Non - Linear Model : Multi-layer Perceptron Multi-Layer Perceptron : Concept Gradient Descent MLP Process
Video - Radial Basic Functions (RBF) Types of Radial Basic Functions Radial Basic Function Gaussian Splines Reflection Question
Video - Support Vector Machines Kernel Hyperplane Support Vector Machines Support Vector Machines Algorithm
Textaul Notes
Unit II - Video
Video 1 - Linear Models
Video 2 - Linear Models
MODULE III : Learning with Trees
Video - Decision Tree
Video - Decision Tree Construction Decision Tree Algorithms
Video - Where to Use KNN Naive Bayes Decision Tree
Video - Decision Tree Decision Tree - Working Decision Tree - Example CART
Textual Notes
Unit III - Video
Video 1 - Learning with Trees
Video 2 - Learning with Trees
Video 3 - Learning with Trees
Video 4 - Learning with Trees
MODULE IV : Activity 2: Creation of Decision Trees to model a real-life world problem
Video - Linear Regression Analysis Linear Regression SPSS Model Comparison Of Bivariate Linear Correlation And Regressions Multivariate Analysis Importance Of MVA Types Of Multivariate Analysis Factor Analysis Path Analysis Manova
Video - The Travelling Salesman Problem Genetic Algorithm Interpretation
Video - Working Principles of Genetic Algorithms Objectives Components of a GA Simple Genetic Algorithm The GA Cycle of Reproduction A Simple Example
Video - Genetic Algorithms Objectives Search Techniques What is Genetic Algorithms Summary
Video - Hidden Markov Models Techniques Ranking Algorithms Statistical Ranking Ranking models Other experiments Involving ranking Selecting ranking techniques
Video - Q Learning R Learning
Video - Reinforcement Learning Different Between R Learning and Supervised Learning
Video - Dimensionality Reduction - Part1
Video - Dimensionality Reduction - Part2
Video - Dimensionality Reduction - Part3
Video - Dimensionality Reduction - Part4
Textual Notes
Unit IV - Video
Video 1 - Creation of Decision Trees to model a real-life world problem
Video 2 - Creation of Decision Trees to model a real-life world problem
Video 3 - Creation of Decision Trees to model a real-life world problem
Video 4 - Creation of Decision Trees to model a real-life world problem
Video 5 - Creation of Decision Trees to model a real-life world problem
Module V : Graphical models
Video - Random Vector The Gauss Markov Linear Model
Video - Markov Chain Markov Decision Process Working of Markov Chain Example Monte Carlo Methods
Video - Graphical Models Types of Graphical Models Bayesian Networks Bayesian Networks Conditional Probability Distribution
Textual Notes
Unit V - Video
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Assignments - October 2023 - Academic Session (July 2022 Batch Only)
PCP LIVE SESSION
MCA Sem III - Machine Learning PCP Session on 12th Jan @9am
PCP Recorded Session
PCP Session On 22nd Jan 2024
PCP Session On 23th Jan 2024
PCP Recorded Session - 24th Jan 2024
PCP Recorded Session - 25th Jan 2024
PCP Recorded Session on 3rd August 2024
PCP Recorded Session on 4th August 2024
PCP Recorded Session on 5th August 2024
PCP Recorded Session on 6th August 2024
PCP Recorded Session on 7th August 2024
Assignments - April 2024 - Academic Session (Jan 2023 Batch & Backlogs )
Machine Learning - MCQ I - April 2024
Machine Learning - Descriptive I - April 2024
Machine Learning - MCQ II - April 2024
Machine Learning - Descriptive II - April 2024
Past Year QB/Model QB
Machine Learning - June 2024
Machine Learning - October 2024
Assignments - November 2024 Academic Session (July 2023 batch & July 2022 batch backlog)
Machine Learning - MCQ I - November 2024
Machine Learning - Descriptive I - November 2024
Machine Learning - MCQ II - November 2024
Machine Learning - Descriptive II - November 2024
Updated PCP Recorded Sessions ( Nov 2024 Academic session Onwards )
Concept of learning task (17th Nov)
Introduction to Python and Introduction to Learning Expression and Arithmetic’s Learning - 24th Nov
Introduction to Linear Models - 1st Dec
Tree and Probabilitistic Models - 25th Dec, 2024
Dimensionality Reduction and Evolutionary Models - 4th Jan, 2024
Graphical Models - Part I - 12th Jan, 2025
Graphical Models - Part II - 12th Jan, 2025
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