Lec02: Implementation of Find-S Algorithm

Lec01: How to Install Jupyter Notebook on Windows 11

Total Delay

Queuing Delay

Processing Delay

Propagation Delay

Transmission Delay

Types of Delays

Lec51: Q-Learning Algorithm with Solved Example

Lec50: Challenges and Applications of Reinforcement Learning

Lec49: Components of Reinforcement Learning

Lec48: Reinforcement v/s Supervised Learning & Reinforcement v/s Unsupervised Learning

Lec47: Scope and Characteristics of Reinforcement Learning

Lec46: Reinforcement Learning-An Overview

Lec45: Single Linkage Hierarchical Clustering using Agglomerative Method

Lec44: K-Means Clustering (partitional clustering) Algorithm with a solved Example

Lec43: Clustering Concepts, Applications, Advantages & Disadvantages, Applications

Lec42: Naive Bayes Algorithm with Solved Example

Lec41: Bayesian Learning | Machine Learning

Lec40: Solved Example on Decision Tree; ID3 Algorithm

Lec39: Decision Tree Concepts and ID3 Algorithm

Lec24: Feature Engineering and Dimensionality Reduction- An Introduction

Lec38: Logistic Regression with solved Example

Lec37: Polynomial Regression with a Solved Example

Lec36: Multiple Linear Regression with Solved Example

Lec35: Linear Regression Matrix Method with solved Example

Lec34: Linear Regression Normal Equation Method - Solved Example

Lec33: Regression Analysis, Linearity, Correlation and Causation

Lec32: Nearest centroid classifier- Algorithm and Solved Example

Lec31: Weighted k-NN - Solved Example

Lec30: Weighted k-NN Algorithm Explanation

Lec29: k-NN Solved Example - Hamming distance as distance metric

Lec28: k-NN(k-Nearest-Neighbor)-Solved Example-Euclidean distance as distance metric

Lec27: Similarity Based Learning and K-NN Algorithm Explaination

Lec26: Find - S Algorithm Explanation and Solved Example

Lec25 : Concept Learning in Machine Learning

Lec23: Matrix Decomposition - LU Method | Machine Learning

Lec22: Gaussian Elimination Method in Machine Learning

Lec21: Gaussian Elimination for Multivariate Data

Lec19: Data Set and Data types in Descriptive Statistics

Lec11b: Data Storage and Representation - Understanding Data(Part-2)

Lec11a: Elements of big Data and Data types- Understanding data(part-1)

Lec18: Covariance and Correlation Coefficient- Bivariate Statistics

Lec17: Univariate, Bivariate and Multivariate Data

Lec16: Z-Score technique in Data Transformations/Data Normalization

Lec15: Min-Max Technique in Data Transformations

Lec 14: Data Smoothing Methods/Binning Techniques | Machine Learning

Lec13: Data Preprocessing- Big Data Analysis Framework | Machine Learning

Lec12: Data Collection; Big Data Analysis framework

Lec10: Applications of Machine Learning | Machine Learning

Lec09: Challenges in Machine Learning | Machine Learning

Lec08: Machine Learning Process

Lec07: Reinforcement Machine Learning | Machine Learning

Lec06: UnSupervised: Clustering, Dimensionality Reduction and Association

Lec05: Regression: A Type of Supervised Machine Learning Algorithm

Lec04: Classification : A type of Supervised Machine Learning Algorithm

Lec03: Machine Learning in relation to other fields | Machine Learning

Lec02: Introduction to Machine Learning | Machine Learning

Lec01: Roadmap for Machine Learning | Machine Learning course

Lec0: Topics in Machine Learning Lecture Series