KnowledgeGATE Bytes
In this channel, Sanchit Sir will provide complete Playlists for various computer science subjects in Hindi for Semester Exams and Various Competitive exams like Gate, ISRO, NIC, RPSC, etc.
11- All About Number Systems: Binary, Decimal, Octal, and Hexadecimal
10 - All About Registers: Types, Functions & Applications | Digital Electronics
9 - All About Counters: Synchronous, Asynchronous & More | Digital Electronics
8 - All About Flip-Flops: SR Flip-Flop, JK Flip-Flops, D Flip-Flops, T Flip-Flop Explained
7 - All About Multiplexer | DeMultiplexer | Decoder | Encoder | Priority Encoder
6 - All About Half Adder | Full Adder | Ripple Adder | Parellel Adder | Look Ahead Carry Adder
5- NAND NOR Universal Gate Complete Discussion in Hindi Functionally Complete Function
4 - K-Map complete discussion in hindiSimplification of Boolean Expression
3- Complete Boolean Expression SOP POS Complementation Dual, Self-Dual for GATE Exam in Hindi
2- All About Logic Gates for GATE EXAM in Hindi
2.7 Support Vector Machine (SVM) | Linear Vs Non-Liner | Polynomial Kernel | Gaussian (RBF) Kernel
2.6 Bayesian Belief Network with solved Example in Machine Learning
2.5 Naive Bayes Classifier with Example in Machine Learning
2.4 Bayes Optimal Classifier with Example in Machine Learning
2.3 Concept Learning in Machine Learning with Simple Example
1-Introduction of Digital Electronics for Gate Exam
2.2 Bayes' Theorem Simplest Explaination with example | Total Probability | Proof
2.1 Regression | Simple Linear Regression | Multiple Linear Regression | Logistic Regression
1.5 Issues | Challenges | Problems in Machine Learning
1.4 Machine Learning Approaches - ANN, Clustering, Classification, Reinforcement Learning, SVM
1.3 Machine Learning - Introduction
1.2 Overview on the history of Machine Learning
3.6 Locally Weighted Regression with Example in Machine Learning
3.5 Instance-Based Learning | K Nearest Neighbour Classification | KNN with Example
3.4 Inductive Bias in Machine Learning with Simple Example
3.3 Decision Tree Learning Algorithm (ID3, C4.5, CART)
3.2 What is Entropy | Entropy for Each Subset | Information Gain | Decision Tree Designing
3.1 What is Decision Tree with Simple Examples in Machine Learning
4.8 Convolutional Neural Networks in Machine Learning with examples convolutional layers stride
4.7 What is Deep Learning with Advantage, Disadvantage and Applications