Канал: CS by Sahil Sharma

Invited Lecture at CGC Jhanjeri Session on CNNs - February 26, 2022

Invited Lecture at CGC Jhanjeri Session on CNNs - February 26, 2022

Revision Class - 2 [Everything about Pointers and Practical Examples] | Dr. Sahil Sharma

Revision Class - 2 [Everything about Pointers and Practical Examples] | Dr. Sahil Sharma

Revision Class - 1 [Conditional Statements, Loops, Arrays, and Strings] | Dr. Sahil Sharma

Revision Class - 1 [Conditional Statements, Loops, Arrays, and Strings] | Dr. Sahil Sharma

Revision Lab - 4 [String Questions, Decimal2Binary, FiboRecursion, Fast Multiply, Structures-Union]

Revision Lab - 4 [String Questions, Decimal2Binary, FiboRecursion, Fast Multiply, Structures-Union]

Revision Lab - 3 [MatrixMul, Linear & Binary Search, Greatest of Three, MinMax in Array, ReverseStr]

Revision Lab - 3 [MatrixMul, Linear & Binary Search, Greatest of Three, MinMax in Array, ReverseStr]

Revision Lab - 2 [Armstrong, Calculator, Array - Sort, Insert, Delete, Reverse, Matrix] | Dr. Sahil

Revision Lab - 2 [Armstrong, Calculator, Array - Sort, Insert, Delete, Reverse, Matrix] | Dr. Sahil

Revision Lab - 1 [EvenOdd, Sum, Prime, Reverse, Palindrome, Fibonacci, Factorial] | Dr. Sahil Sharma

Revision Lab - 1 [EvenOdd, Sum, Prime, Reverse, Palindrome, Fibonacci, Factorial] | Dr. Sahil Sharma

Lab - File Handling in C Programming

Lab - File Handling in C Programming

Linear Search, Binary Search, and Strings in C Programming | Dr. Sahil Sharma

Linear Search, Binary Search, and Strings in C Programming | Dr. Sahil Sharma

Lab - Functions and Recursion in C | Dr. Sahil Sharma

Lab - Functions and Recursion in C | Dr. Sahil Sharma

19 - K Means Clustering | Dr. Sahil Sharma | Machine Learning Practical Series

19 - K Means Clustering | Dr. Sahil Sharma | Machine Learning Practical Series

Lecture 31 - Neural Networks | Dr. Sahil Sharma

Lecture 31 - Neural Networks | Dr. Sahil Sharma

Lecture 30 - Genetic Algorithms | Dr. Sahil Sharma

Lecture 30 - Genetic Algorithms | Dr. Sahil Sharma

Lecture 29 - Apriori Algorithm | Dr. Sahil Sharma

Lecture 29 - Apriori Algorithm | Dr. Sahil Sharma

Lecture 28 - Association Rule Learning and Naive Algorithm | Dr. Sahil Sharma

Lecture 28 - Association Rule Learning and Naive Algorithm | Dr. Sahil Sharma

18 - Soft Linear SVM Implementation for Breast Cancer Detection | Dr. Sahil Sharma | ML Practical

18 - Soft Linear SVM Implementation for Breast Cancer Detection | Dr. Sahil Sharma | ML Practical

Lecture 27 - Kernel K-means and Hierarchical Clustering | Dr. Sahil Sharma

Lecture 27 - Kernel K-means and Hierarchical Clustering | Dr. Sahil Sharma

Lecture 26 - K-means, K-median, K-mode, K-Prototype | Dr. Sahil Sharma

Lecture 26 - K-means, K-median, K-mode, K-Prototype | Dr. Sahil Sharma

Lecture 25 - Types of Clustering and Introduction to K-Means Clustering | Dr. Sahil Sharma

Lecture 25 - Types of Clustering and Introduction to K-Means Clustering | Dr. Sahil Sharma

Lecture 10 - Bitwise Operators, Precedence and Associativity | 1ME4-6 | 29 October 2021

Lecture 10 - Bitwise Operators, Precedence and Associativity | 1ME4-6 | 29 October 2021

Lab 04 - 1COE09 - For, While and Do While Loop, Armstrong, and Prime Numbers | 28 October 2021

Lab 04 - 1COE09 - For, While and Do While Loop, Armstrong, and Prime Numbers | 28 October 2021

Lab 03 - 1COE06 - Bitwise AND, Ternary, Armstrong, Prime, and Fibonacci | 28 October 2021

Lab 03 - 1COE06 - Bitwise AND, Ternary, Armstrong, Prime, and Fibonacci | 28 October 2021

Lab 03 - 1COE19 - 27 October 2021

Lab 03 - 1COE19 - 27 October 2021

Lab 04 - 1COE2 - 26 October 2021

Lab 04 - 1COE2 - 26 October 2021

Lecture 09 - Assignment, Relational, Logical and Bitwise Operators | 1ME4-6 | 28 October 2021

Lecture 09 - Assignment, Relational, Logical and Bitwise Operators | 1ME4-6 | 28 October 2021

Lecture 10 - Operators in C Programming | 1ME1-3 | 26th October 2021

Lecture 10 - Operators in C Programming | 1ME1-3 | 26th October 2021

Lecture 9 - Data Types, Variables, Constants, I/O, and Intro to Operators | 1ME1-3 | 25 October 2021

Lecture 9 - Data Types, Variables, Constants, I/O, and Intro to Operators | 1ME1-3 | 25 October 2021

Lecture 11 - Operators in C Continued and Precedence in C Programming | 1ME1-3 | 27 October 2021

Lecture 11 - Operators in C Continued and Precedence in C Programming | 1ME1-3 | 27 October 2021

Lecture 8 - Data Types, Variables, Constants, I/O, and Intro to Operators | 1ME4-6 | 25 October 2021

Lecture 8 - Data Types, Variables, Constants, I/O, and Intro to Operators | 1ME4-6 | 25 October 2021

Lecture 07 - Life Cycle of C Program, Keywords, Identifiers, Datatypes | 1ME4-6 | 22 October 2021

Lecture 07 - Life Cycle of C Program, Keywords, Identifiers, Datatypes | 1ME4-6 | 22 October 2021

Lecture 06 - 32-bit Floating Point & Structure of C Program | 21st October 2021 | Dr. Sahil Sharma

Lecture 06 - 32-bit Floating Point & Structure of C Program | 21st October 2021 | Dr. Sahil Sharma

Lab 03 - 1COE09 - Bitwise AND, Ternary, Greatest of 3, Midpoint, Sum of digits, Reverse of Number

Lab 03 - 1COE09 - Bitwise AND, Ternary, Greatest of 3, Midpoint, Sum of digits, Reverse of Number

Lecture 08 - Life Cycle of C Program, Keywords, Identifiers, Datatypes | UTA003 - 19th October 2021

Lecture 08 - Life Cycle of C Program, Keywords, Identifiers, Datatypes | UTA003 - 19th October 2021

Lab 03 - 1COE2 - Bitwise AND, Ternary Operator, Midpoint, Celsius to Fahrenheit - 19 October 2021

Lab 03 - 1COE2 - Bitwise AND, Ternary Operator, Midpoint, Celsius to Fahrenheit - 19 October 2021

Lecture 07 - Basics about C Program | UTA003 | Dr. Sahil Sharma - 18th October 2021

Lecture 07 - Basics about C Program | UTA003 | Dr. Sahil Sharma - 18th October 2021

Lab 02 - 1COE9 - Quadratic Roots, Swapping, Left - Right Shift, Ternary Operator - 14 October 2021

Lab 02 - 1COE9 - Quadratic Roots, Swapping, Left - Right Shift, Ternary Operator - 14 October 2021

Lecture 5 - Pseudo Code, Language Generations, Program Life Cycle, Malware, 32-bit Floating Point

Lecture 5 - Pseudo Code, Language Generations, Program Life Cycle, Malware, 32-bit Floating Point

Lecture 4 - Computer Memory, Software, Algorithm, Flowcharts, and Pseudo Code | 13 October 2021

Lecture 4 - Computer Memory, Software, Algorithm, Flowcharts, and Pseudo Code | 13 October 2021

Lab 02 - 1COE6 - Discussion on Assignment 2 - 13 October 2021

Lab 02 - 1COE6 - Discussion on Assignment 2 - 13 October 2021

Lecture 6 - 32 bit Floating Point Representation and C Program Structure | 1ME1-3 | Dr. Sahil Sharma

Lecture 6 - 32 bit Floating Point Representation and C Program Structure | 1ME1-3 | Dr. Sahil Sharma

Lab 02 - 1COE19 - Discussion on Assignment 1 and 2 - 13 October 2021

Lab 02 - 1COE19 - Discussion on Assignment 1 and 2 - 13 October 2021

Lecture 05 - Algo, Flowchart, Pseudo Code, and Malware | UTA003 | Dr. Sahil Sharma - 12 October 2021

Lecture 05 - Algo, Flowchart, Pseudo Code, and Malware | UTA003 | Dr. Sahil Sharma - 12 October 2021

Lab 02 - 1COE2 - Discussion on Assignment 1 and 2 - 12 October 2021

Lab 02 - 1COE2 - Discussion on Assignment 1 and 2 - 12 October 2021

Lecture 04 - Base Conversions & Memory Classification | UTA003L | Dr. Sahil Sharma - 11 October 2021

Lecture 04 - Base Conversions & Memory Classification | UTA003L | Dr. Sahil Sharma - 11 October 2021

17 - ID3 and CART Decision Tree Implementation| Dr. Sahil Sharma | Machine Learning Practical Series

17 - ID3 and CART Decision Tree Implementation| Dr. Sahil Sharma | Machine Learning Practical Series

16 - Naive Bayes Implementation | Dr. Sahil Sharma | Machine Learning Practical Series

16 - Naive Bayes Implementation | Dr. Sahil Sharma | Machine Learning Practical Series

15 - K - Nearest Neighbours Implementation | Dr. Sahil Sharma | Machine Learning Practical Series

15 - K - Nearest Neighbours Implementation | Dr. Sahil Sharma | Machine Learning Practical Series

Lecture 03 - Signed and Unsigned Binary Numbers + Base 2, 8, and 16 Conversions | 08 October 2021

Lecture 03 - Signed and Unsigned Binary Numbers + Base 2, 8, and 16 Conversions | 08 October 2021

Lab 01 - 1COE9 - Introduction to C Programming - 07 October 2021 | Dr. Sahil Sharma

Lab 01 - 1COE9 - Introduction to C Programming - 07 October 2021 | Dr. Sahil Sharma

Lecture 02 - Introduction to Binary Number System | Dr. Sahil Sharma | 06 October 2021

Lecture 02 - Introduction to Binary Number System | Dr. Sahil Sharma | 06 October 2021

Lab 01 - 1COE6 - Introduction to C Programming - 06 October 2021 | Dr. Sahil Sharma

Lab 01 - 1COE6 - Introduction to C Programming - 06 October 2021 | Dr. Sahil Sharma

Lecture 24 - Introduction to Clustering and its Evaluation Metrics | Dr. Sahil Sharma

Lecture 24 - Introduction to Clustering and its Evaluation Metrics | Dr. Sahil Sharma

Lecture 01 - Introduction to C Programming | Dr. Sahil Sharma | 06 October 2021

Lecture 01 - Introduction to C Programming | Dr. Sahil Sharma | 06 October 2021

Lab 01 - 1COE19 - Introduction to C Programming - 06 October 2021 | Dr. Sahil Sharma

Lab 01 - 1COE19 - Introduction to C Programming - 06 October 2021 | Dr. Sahil Sharma

Lecture 03 - Introduction to Binary Number System | UTA003L | Dr. Sahil Sharma - 06 October 2021

Lecture 03 - Introduction to Binary Number System | UTA003L | Dr. Sahil Sharma - 06 October 2021

Lecture 01 - Introduction to Machine Learning

Lecture 01 - Introduction to Machine Learning

Lecture 02 - Introduction to Machine Learning Contd.

Lecture 02 - Introduction to Machine Learning Contd.

Lecture 03 - Types of Machine Learning

Lecture 03 - Types of Machine Learning

Lecture 05 - Data Preprocessing - Continued

Lecture 05 - Data Preprocessing - Continued

Lecture 06 - Data Integration and Reduction

Lecture 06 - Data Integration and Reduction

Lecture 07 - Feature Selection and Extraction

Lecture 07 - Feature Selection and Extraction

Lecture 08 - Principal Component Analysis (PCA) and Singular Value Decomposition (SVD)

Lecture 08 - Principal Component Analysis (PCA) and Singular Value Decomposition (SVD)

Lecture 09 - Linear Discriminant Analysis (LDA) and Sampling Techniques in Machine Learning

Lecture 09 - Linear Discriminant Analysis (LDA) and Sampling Techniques in Machine Learning

Lab 04 - Principal Component Analysis and SVD

Lab 04 - Principal Component Analysis and SVD

Lab 01 - Introduction to Python

Lab 01 - Introduction to Python

Lecture 10 - Sampling Methods and Linear Regression

Lecture 10 - Sampling Methods and Linear Regression

Lecture 11 - Linear Regression - Gradient Descent Optimization

Lecture 11 - Linear Regression - Gradient Descent Optimization

Lecture 12 - Linear Regression - Problems and Solutions

Lecture 12 - Linear Regression - Problems and Solutions

Lab 05 - Least Square Error (LSE) and Gradient Descent Optimization (GDO) based Linear Regression

Lab 05 - Least Square Error (LSE) and Gradient Descent Optimization (GDO) based Linear Regression

Lecture 13 - Regularization and Regression Evaluation Metrics

Lecture 13 - Regularization and Regression Evaluation Metrics

Lecture 14 - Classification and Logistic Regression

Lecture 14 - Classification and Logistic Regression

Lab 06 - Bag of Words, TF-IDF, Ridge and LASSO Regression, RidgeCV, and LassoCV | Dr. Sahil Sharma

Lab 06 - Bag of Words, TF-IDF, Ridge and LASSO Regression, RidgeCV, and LassoCV | Dr. Sahil Sharma

Lecture 15 - Logistic Regression Contd and Classification Evaluation Metrics | Dr. Sahil Sharma

Lecture 15 - Logistic Regression Contd and Classification Evaluation Metrics | Dr. Sahil Sharma

Lecture 16 - Classification Evaluation Metrics Contd and Naive Bayes Introduction | Dr. Sahil Sharma

Lecture 16 - Classification Evaluation Metrics Contd and Naive Bayes Introduction | Dr. Sahil Sharma

Lecture 17 - Naive Bayes Continued and Introduction to K-Nearest Neighbour (KNN) | Dr. Sahil Sharma

Lecture 17 - Naive Bayes Continued and Introduction to K-Nearest Neighbour (KNN) | Dr. Sahil Sharma

Lecture 18 - K Nearest Neighbour Continued and Decision Tree (ID3) Introduction | Dr. Sahil Sharma

Lecture 18 - K Nearest Neighbour Continued and Decision Tree (ID3) Introduction | Dr. Sahil Sharma

Lab 02 - Numpy and Basics of Pandas | Dr. Sahil Sharma

Lab 02 - Numpy and Basics of Pandas | Dr. Sahil Sharma

Lab 03 - Handling Missing Values | Dr. Sahil Sharma

Lab 03 - Handling Missing Values | Dr. Sahil Sharma

Lecture 19 - ID3 Continued and C4.5 Decision Tree | Dr. Sahil Sharma

Lecture 19 - ID3 Continued and C4.5 Decision Tree | Dr. Sahil Sharma

Lecture 20 - CART Decision Tree and Introduction to Random Forest | Dr. Sahil Sharma

Lecture 20 - CART Decision Tree and Introduction to Random Forest | Dr. Sahil Sharma

Lecture 21 - Random Forest | Dr. Sahil Sharma

Lecture 21 - Random Forest | Dr. Sahil Sharma

Lecture 22 - Random Forest Example and Hard Support Vector Machines (SVM) | Dr. Sahil Sharma

Lecture 22 - Random Forest Example and Hard Support Vector Machines (SVM) | Dr. Sahil Sharma

Lecture 23 - Soft Linear SVM and Non Linear SVM | Dr. Sahil Sharma

Lecture 23 - Soft Linear SVM and Non Linear SVM | Dr. Sahil Sharma

Lecture 02 - Structure of C Program - scanf/printf | UTA003L | Dr. Sahil Sharma - 05 October 2021

Lecture 02 - Structure of C Program - scanf/printf | UTA003L | Dr. Sahil Sharma - 05 October 2021

Lecture 01 - Introduction to C Programming | UTA003L | Dr. Sahil Sharma - 04 October 2021

Lecture 01 - Introduction to C Programming | UTA003L | Dr. Sahil Sharma - 04 October 2021

Lab 01 - 1COE2 - Introduction to C Programming - 05 October 2021 | Dr. Sahil Sharma

Lab 01 - 1COE2 - Introduction to C Programming - 05 October 2021 | Dr. Sahil Sharma

14 - Logistic Regression using scikit-learn | Dr. Sahil Sharma | Machine Learning Practical Series

14 - Logistic Regression using scikit-learn | Dr. Sahil Sharma | Machine Learning Practical Series

13 - Principal Component Analysis on IRIS | Dr. Sahil Sharma | Machine Learning Practical Series

13 - Principal Component Analysis on IRIS | Dr. Sahil Sharma | Machine Learning Practical Series

12 - Pandas - Text Methods | Dr. Sahil Sharma | Machine Learning Practical Series

12 - Pandas - Text Methods | Dr. Sahil Sharma | Machine Learning Practical Series

11 - Pandas - Combining DataFrames | Dr. Sahil Sharma | Machine Learning Practical Series

11 - Pandas - Combining DataFrames | Dr. Sahil Sharma | Machine Learning Practical Series

10 - Pandas - GroupBy Operations | Dr. Sahil Sharma | Machine Learning Practical Series

10 - Pandas - GroupBy Operations | Dr. Sahil Sharma | Machine Learning Practical Series

09 - Pandas - Missing Data | Dr. Sahil Sharma | Machine Learning Practical Series

09 - Pandas - Missing Data | Dr. Sahil Sharma | Machine Learning Practical Series

08 - Pandas - Conditional Filtering, Method Calls, and Description Sorting | Dr. Sahil Sharma

08 - Pandas - Conditional Filtering, Method Calls, and Description Sorting | Dr. Sahil Sharma

07 - Introduction to Pandas | Dr. Sahil Sharma | Machine Learning Practical Series

07 - Introduction to Pandas | Dr. Sahil Sharma | Machine Learning Practical Series

06 - Numerical Python - NumPy | Dr. Sahil Sharma | Machine Learning Practical Series

06 - Numerical Python - NumPy | Dr. Sahil Sharma | Machine Learning Practical Series

05 - Regular Expressions in Python | Dr. Sahil Sharma | Machine Learning Practical Series

05 - Regular Expressions in Python | Dr. Sahil Sharma | Machine Learning Practical Series

04 - Date Time and Timezones in Python | Dr. Sahil Sharma | Machine Learning Practical Series

04 - Date Time and Timezones in Python | Dr. Sahil Sharma | Machine Learning Practical Series

03 - Data Structures in Python | Dr. Sahil Sharma | Machine Learning Practical Series

03 - Data Structures in Python | Dr. Sahil Sharma | Machine Learning Practical Series

02 - Basics of Python - Part 2 | Dr. Sahil Sharma | Machine Learning Practical Series

02 - Basics of Python - Part 2 | Dr. Sahil Sharma | Machine Learning Practical Series

01 - Basics of Python - Part 1 | Dr. Sahil Sharma | Machine Learning Practical Series

01 - Basics of Python - Part 1 | Dr. Sahil Sharma | Machine Learning Practical Series

Lecture 04 - Types of ML Contd. and Data Preprocessing Introduction

Lecture 04 - Types of ML Contd. and Data Preprocessing Introduction

201. NLP - Fundamentals of Natural Language Processing

201. NLP - Fundamentals of Natural Language Processing

110. Computer Vision - Face Verification

110. Computer Vision - Face Verification

109. Computer Vision - Face Recognition

109. Computer Vision - Face Recognition

108. Computer Vision - Transfer Learning - Inception

108. Computer Vision - Transfer Learning - Inception

107. Computer Vision - Transfer Learning - AlexNet, VGG16, ResNet

107. Computer Vision - Transfer Learning - AlexNet, VGG16, ResNet

106. Computer Vision - Convolutional Neural Networks

106. Computer Vision - Convolutional Neural Networks

105. Computer Vision - Optimization and Regularization in Neural Networks

105. Computer Vision - Optimization and Regularization in Neural Networks

104 . Computer Vision - Neural Networks

104 . Computer Vision - Neural Networks

103. Computer Vision - The Perceptron

103. Computer Vision - The Perceptron

102. Computer Vision - Basics of Image Processing and Formation

102. Computer Vision - Basics of Image Processing and Formation

101. Computer Vision - Introduction and Goal

101. Computer Vision - Introduction and Goal

Digit Recognizer Kaggle Challenge (Test Accuracy: 99.275%)

Digit Recognizer Kaggle Challenge (Test Accuracy: 99.275%)

Virtual Memory and Memory Management Hardware

Virtual Memory and Memory Management Hardware

LSTM using CIFAR-10 Dataset

LSTM using CIFAR-10 Dataset

Transfer Learning Using Inception Model in Keras

Transfer Learning Using Inception Model in Keras

MNIST Digit Classification using CNN in Keras

MNIST Digit Classification using CNN in Keras

MNIST Digit Multiperceptron in Keras

MNIST Digit Multiperceptron in Keras

Binary Classification using Logistic Regression

Binary Classification using Logistic Regression

Linear Regression in Deep Learning

Linear Regression in Deep Learning

TensorFlow Basics

TensorFlow Basics

Deep Learning Basics - Vectorization and Broadcasting

Deep Learning Basics - Vectorization and Broadcasting

Introduction to ARM Programming with Code for Addition and Subtraction

Introduction to ARM Programming with Code for Addition and Subtraction

Asynchronous Counters in Verilog Programming

Asynchronous Counters in Verilog Programming

D Flip Flop in Verilog Programming

D Flip Flop in Verilog Programming

1:4 Demultiplexer in Verilog Programming

1:4 Demultiplexer in Verilog Programming

4:1 Multiplexer in Verilog Programming

4:1 Multiplexer in Verilog Programming

BCD to Excess 3 Code Converter | Verilog Programming

BCD to Excess 3 Code Converter | Verilog Programming

Full Subtractor in Verilog Programming

Full Subtractor in Verilog Programming

Half Subtractor in Verilog Programming

Half Subtractor in Verilog Programming