Preview Data Science Combo Course

Data Science Combo Introduction (Start From Here)

Connect with Teaching Assistant for Doubt Clearance.

How To Connect Teaching Assistant (TA) ?

How To Follow Course Structure ?

How To Get Course Certificate ?

How To Submit Resume For Review ?

How To Apply For Internship ?

Understand The Individual Course Structure

Please Read

How to start with Python Module ?

Structure of SQL Module

Structure of ML, DL, Maths & Stats Module

Fundamentals of AI and Data Science(Optional)

1. Intro To Artificial Intelligence

2. Intro To Machine Learning

3.What is Data ?

4. Brief Intro To ML Algorithms

5. Life Cycle of Data Science & ML Project

6. What is Deep Learning ?

7. Real World Implementation of AI

8. Different Roles in Data Science

Core Python

Video 0: Importance of programming

Python Basics Assignment(Download this first)

Video 1: Print

Video 2: Comments

Video 3: Variables

Video 4: Datatypes

Video 5: TypeCasting

Video 6: ArithmeticOperation

Video 7: Indexing & Slicing

Video 8: String Operations

Video 9: Input Output

Video 10: Math Function

Video 11 : BinaryNumber(optional for data science)

Video 12: Python Operator

Video 13 : Data Structures Introduction

Video 14.1 : List Part 1

Video 14.2 : List Part 2

Video 14.3 : List Part 3

Video 15 : IF ELSE

Video 15.1: Statement & Indentation

Video 16: Loops

Video 17: Loop Problem Statements in Python , Nested Loop Examples (Optional)

Video 18: Functions in Python , User Defined Functions

Video 19: Top 5 Python Functions YOU MUST KNOW

Python Basics Explanation Video

Python reloaded assignment(download this)

Video 20: Set

Video 21: Dictionary

Video 22: Tuple

Video 23: List Dict Set Comprehensions in Python(More Examples)

VIdeo 24: DECODING RECURSION in Python

Python_Reloaded Assignment Solution(Explanation)

Video 25: File Handling

Video 26: Error Handling

Data Structures Assignment(Download this first)

Data structure solution

Video 0 : Python_Intermediate_Tutorial

Video 1: Python Intermediate Intro

Python Intermediate Assignment(Download this first)

Video 2: Duplicate, Occurence, Factorial Problem

Video 3: Reversing a Number

Video 4: IP Address Problem

Video 5: Removing Punctuation, 2-D Array

Video 6: Cost of Removal Problem

Video 7: Smallest String , Count Code

Video 8: Sum of the Series, Count of Vowels

Video 9: Longest Substring

Video 10: Hangman

Video : Regex Tutorial

Regex assignment

Regex_Explanation_Video

Hackerank Section

Video : Create Account (Hackerrank)

Hacker_rank Challenge Assignment

Problem Sol 1 : PythonIfElse

Problem Sol 2 : PythonArithOper

Problem Sol 3 : PythonPrintFun

Problem Sol 4 : PythonWriteAFuncLeapYr

Problem Sol 5 : ListComprehension

Problem Sol 6: RunnerUp

Problem Sol 7: NestedLists

Problem Sol 8: FindingPercentage

Problem Sol 9: Lists

Problem Sol 10: Tuples

Problem Sol 11: MinionGame

Problem Sol 12: DoorMatDesign

Problem Sol 13: MergeTool

Problem Sol 14: findaString

Problem Sol 15: NoIdea

Problem Sol 16: SymDiffSet

Problem Sol 17: LambdaMap

Problem Sol 18: ValidEmail

Problem Sol 19: ReduceFunc

Problem Sol 20: CollectionCounter

Probloem Sol 21 : NamedTuples

Problem Sol 22 : DefaultDict

Hackerank All Problem Solution of Assignment

Python Notes Link

Python For Data Science

Numpy

Introduction To NumPy

Numpy assignment(Download this first)

Video 1: Numpy Array Dimensions

Video 2: List Vs Numpy

Video 3: Numpy array Reshaping

Video 4: Numpy Array Indexing

Video 5: Numpy Slicing Operations

Video 6: Numpy View Vs Copy

Video 7 : Numpy Hstack Vs Vstack

Video 8: Numpy Concatenation

Video 9: Numpy Insert Append Delete

Complete numpy tutorial(Add on)

Numpy Assignment solution

Pandas

Introduction To Pandas

Pandas assignment(download this first)

Video 1: Pandas Series

Video 2: Pandas DataFrame

Video 3: Pandas Concatenation

Video 4: Top Pandas Commands in Data Science

Video 5: Indexing DataFrame

Video 6: How to upload and read data in colab

Video 7: Pandas Groupby

Video 8: Pandas Date Range

Pandas creating and reading CSV files in Jupyter notebook(Add on)

Black Friday Case Study

Pandas Assignment Solution

Data Cleaning

Data Cleaning(Download this first)

Video 1: Introduction of Data Cleaning

Video 2: nan special case 1

Video 3: nan special case 2

Video 4: basic missing value treatment

Video 5: Ffill, Bfill & KNNImputer

Video 6: deciding imputation technique

Video 7: Dataframe Iterations

Video 8: Pandas Function

Data Cleaning Assignment Solution

EDA

Intro To EDA

Eda assignment(download this first)

Video 1: Deleting rows and columns from the Dataframe

Video 2: Duplicate Values

Video 3: Missing Value Handling

Video 4: Removing Outliers from the DataFrame

Video 5: IQR Outlier & Z score

Video 6: Data Visualisation by Different Plots

Video 7: Matplotlib(creating visual, labels,subplot)

Video 8: Matplotib part 2(Object Oriented way, fonts, fig_size,dpi)

Video 9: Matplotlib part 3(Legends,labels)

Video 10 : Matplotlib part 4(barchart, scatter plot chart,histogram,piechart)

Video 11: Seaborn tutorial part 1

Video 12: Seaborn tutorial part 2

EDA Assignment Explanation Part 1

EDA Assignment Explanation Part 2

Quiz Section

Python Quiz

Data Structure Quiz

NumPy Quiz

Pandas Quiz

DSA

Introduction To Classes

Scope of Variables, Inheritance in Classes

Download Time Complexity Assignment

Time Complexity part 1

Time Complexity part 2

Time Complexity Last Question solution

Download Array Assignement

Problem 1: Explanation

Problem 1: Code Explanation

Problem 2: Explanation

Problem 2: Code Explanation

Solved Problem 3: Clockwise Rotated Matrix

Solved Problem 4: Sum of two elements

Solved Problem 5: Duplicate Numbers

Solved Problem 6: Running Sums

Practice Problem solution-1

Practice Problem solution-2 (array)

Practice Problem solution-3 (array)

Practice Problem solution-4 (array)

Practice Problem solution-5 (array)

Practice Problem solution-6 (array)

Download Recursion Assignment

Solved Problem 1: Sum of All Numbers

Solved Problem 2: Nth Fibonacci Number

Solved Problem 3: Reversed Array

Solved Problem 4: Subsequence

Solved Problem 5: Unique Combination

Solved Problem 6: Possible Permutation

Practice Problem -1 (recursion)

Practice Problem -2 (recursion)

Practice Problem -3 (recursion)

Practice Problem -4 (recursion)

Download Sorting Assignment

Video 1: Bubble Sort

Video 2: Insertion Sort

Video 3: Selection Sort

Video 4: Merge Sort

Video 5: Quick Sort

Video 6: Linear Search

Video 7 : Binary Search

Practice Problem Solution-1 (sorting)

Practice Problem Solution-2 (sorting)

Practice Problem Solution-3 (sorting)

Download Linkedlist Assignment

Linked List Introduction

Solved Problem 1: Reverse Singly Linked list

Solved Problem 2: Middle Node

Solved Problem 3: Deleting Node

Solved Problem 4: Sum of 2 number

Solved Problem 5: Cyclic Linkedlist

Pracrice Problem Solution 1 (linkedlist)

Pracrice Problem Solution 2 (linkedlist)

Pracrice Problem Solution 3 (linkedlist)

Download Stack&Queue Assignment

Video 1: Introduction of Stacks and Queues

Video 2: Stack Problem

Video 3: Queue Problem

Video 4: Balanced Parentheses Problem

Video 5: Reversed Polish Problem

Solved Practice Problem-1 (stack&queue)

Solved Practice Problem-2 (stack&queue)

Download Trees Assignment

Video 1: Trees Introduction

Video 2: Inorder Traversal

Video 3: Preorder Traversal

Video 4: Postorder Traversal

Video 5: Level Order Travesal

Video 6 : Max Depth Problem

Video 7: Diameter Problem

Video 8: Identical Problem

Video 9: Left View Problem

Video 10: Lowest Common Ancestor Problem

Practice Problem Solution-1 (tree)

Practice Problem Solution-2 (tree)

Practice Problem Solution-3 (tree)

Practice Problem Solution-4 (tree)

Download Dynamic Assignment

Solved Problem 1: Fibonacci Number

Solved Problem 2: Stairs Problem

Solved Problem 3: Subsequence

Solved Problem 4: Frog Jump

Solved Problem 5: Unique path

Solved Problem 6: Min Cost path

Solved Problem 7: Knapsack problem

Practice Problem Solution 1 (dynamic)

Download Graph Assignment

Video 1 : Graph Introduction

Video 2 : Graph Represenation

Solved Problem 1 : Breadth First Search Using Graph

Solved Problem 2 : Depth First Search Using Graph

Solved Problem 3: Cyclicn / Non-Cyclic Using DFS

Solved Problem 4 : Bipartite Problem Using DFS

Graph Practice Problems Explanation

Machine Learning

Feature Selection

Download Feature Selection Assignment

Video 1: Feature Selection Techniques

Video 2: Identify and Dropping Missing Values

Video 3: Variance Threshold Removal

Video 4: Difference between fit transform fit_transform predict

Video 5: One Way ANOVA

Video 6: Recursive Feature Elimination

Video 7: Model Based Feature Selection

Video 8: Variance Inflation Factor

Feature Selection Solution

Feature Selection Solution With Explanation

Feature Engineering

Download Feature Engineering Assignment

Video 1: Creating New Column

Video 2: DropNa

Video 3: Mean Method FillNa

Video 4: Handling Missing Values Categorical Data

Video 5: Outlier Detection and Removal using Standard Deviation and Z Score

Video 6: Outlier Detection and Removal using Pandas

Video 7: Data Pre-Processing in Data Mining

Video 8 : Binning

Video 9 : Encoding Categorical Data

Video 10 : How to Transform Data to Better Fit The Gaussian Distribution

Video 11 : Datetime Module

Feature Engineering Solution

Feature Engineering Explanation Video

Linear Regression

Download Linear Regression Assignment

Video 1 : Assumptions of Linear Regression

Video 2 : .Linear Regression-Splitting and describing dataframe

Video 3: Linear Regression-EDA on dataset

Video 4 : Linear Regression-Reshaping concept

Video 5 : Linear Regression-Fitting The Regression Model

Video 6 : Linear Regression-Metrics In Regression

Video 7 : Linear Regression-Residual Errors

Linear Regression Assignment Explanation Video

Multiple Linear Regression

Download Multiple Linear Regression Assignment

Video 1 : Map Function

Video 2 : Get Dummies

Video 3 : Standard vs Normal

Video 4 : Building Model

Video 5 : Multicollinearity

Video 6 : Metrics

Multiple Regression Assignment Explanation Video

Advanced Linear Regression

Download Adv Linear Regression Assignment

Video 1: Advanced Linear Regression Tutorial

Video 2: ML Pipeline Tutorial

Video 3: Regression Types

Advance Linear Regression Solution

Advanced Regression Explanation Video

Logistic Regression

Download Logistic Regression Assignment

Video 1 : Logistic Regression Intuition Part 1

Video 2 : Logistic Regression Intuition Part 2

Video 3 : Logistic Regression Intuition Part 3

Video 4 : Normalization & Standardization

Video 5 : Logistic Regression by Statsmodel (Theory)

Video 6: Logistic Regression Statsmodel(Practical)

Video 7 : Dropping Highly Correlated Variables

Video 8 : Variance Inflation Factor

Video 9 : Performace Measure for Classification(theory)

Video 10 : Classification Model Evaluation(code)

Video 11 : ROC-AUC

Logistic Regression Solution

Logistic Regression Explanation Video

PCA

Download PCA Assignment

Video 1 : PCA Theory Part 1

Video 2: PCA Theory part 2

VIdeo 3 : PCA Implementation

Video 4 : PCA Visualization

PCA Solution

PCA Assignment Explanation Theory

PCA Assignment Explanation Coding

KNN

Download KNN Assignment

Video 1 : KNN theory

Video 2 : KNN Implementation

KNN Solution

KNN Assignment Explanation

Decision Tree

Download Decision Tree Assignment

Video 1 : Decision Tree Theory Part 1

Video 2 : Decision Tree Theory Part 2

Video 3 : Decision Tree Theory Part 3

Video 4 : Decision Tree Theory Part 4

Video 5 : Visualizing Decision Tree

Video 6 : Grid Search CV

Video 7 : Post Pruning Decision Tree

Decision Tree Assignment Explanation

Naive Bayes

Download Naive Bayes Assignment

Video 1 : NaiveBayes Intro

Video 2 : Text Analytics(Count Vectorizer)

Video 3 : Bernoulli Naive Bayes

Video 4 : Confusion Matrix

Video 5 : sensitivity & specificity

Video 6: ROC AUC.

Video 7 : Multinomial Naive bayes

Video 8: Gaussian Naive bayes

Naive Bayes Solution

Bagging

Download Bagging Assignment

Video 1 : Bagging Intuition

Video 2 : Pipeline

Video 3 : Scikit Learn Ensemble Learning

Video 4 : Random Forest

Video 5 : Extra Tree

Video 6 : Hyperparameter Tuning using Randomized Search CV

Bagging Solution

Bagging Assignment Explanation

Boosting

Download Boosting Assignment

Video 1: Boosting

Video 2 : Adaptive Boosting

Video 3 : Gradient Boosting

Video 4 : XGBOOST

Video 5 : CatBoost Training on GPU

boosting solution

Clustering

Download Clustering Assignment

Video 1 : Unsupervised Learning Introduction

Video 2 : Unsupervised practical

Video 3 : Hopkin Statistics Intuition

Video 4 : kmean Intuition

Video 5 : Silhouette (clustering)- Validating Clustering Models

Video 6 : K-Means Clustering with Elbow Method

Video 7 : Clustering - Hierarchical clustering (Theory)

Video 8: Hierarchical Practical

Video 9 : dbscan intuition part 1

Video 10 : dbscan intuition part 2

Video 11 : DBSCAN Clustering coding

Video 12: Mean Shift Clustering

Video 13: Optics Clustering

Video 14 : Clustering - Gaussian Mixture Models

clustering solution

Support Vector Machine

Download SVM Assignment

Video 1 : SVM Intuition

Video 2 : Hyperparameter Tuning SVM using GridSearchCV

svm solution

Hypothesis Testing

Download Hypothesis Assignment

Video 1: Hypothesis Intuition

Video 2: Null & Alternate Hypothesis

Video 3: Terms related to Hypothesis Testing

Video 4: Hypothesis Example 1

Video 5: Recap of Example 1

Video 6: Hypothesis Example 2

Video 7: Z test

Video 8: T test

Video 9: Degrees of Freedom

Video 10: One sample t test

Video 11: Two sample T test

Video 12: Paired T-test

Video 13: Chi-Sqare test 1

Video 14-Chi Square test 2

Video 15-ANOVA introduction

Video 16: Types of ANOVA

Hypothesis Testing Solution

Gradient Descent

Download Gradient Descent Assignement

Video 1 : Gradient descent intuition

Video 2 : Gradient Descent on Linear Regression

Gradient Descent Solution

Model Deployment

Simple Linear Regression Deployment

Multiple linear regression deployment

Machine Learning Projects

Employee Attrition Problem

Problem statement explanation(EMp Attrition)

Download Employee Attrition File

Dataset Overview

Categorical Column + Correlation Matrix

Chi Square Test

EDA

Variance Inflation Factor

ANOVA + Dendogram

Model Building

Hyperparameter Tuning + Summary

Chronic Kidney Disease Problem

Problem_Explanation

Download Chronic File

Chronic Dataset Overview

Data Cleaning Part-1

Data Cleaning Part-2

Chronic EDA

Imputing And Encoding

Choosing Best Model

HackerEarth Machine Learning | Exhibit Art ( Finance )

hackerearth exhibit art project explanation withcode

MachineHack ML | Merchandise Popularity Prediction ( Marketing )

Merchandise Popularity Prediction project explanation withcode

Financial News Headlines Data | Sentiment Analysis( Finance )

Financial News Headline Explanation Video

ODI Cricket Match Winner Prediction ( Sports )

ODI cricket match winner prediction soln video

Steam Video Games Dataset | Recommender System

Steam video game recommender system Solution video

Ethereum Fraud Detection

ethereum solution video

Electrical Fault Detection - IOT Dataset

electrical fault solution video

Quora Question Pair

Video 0: Quora Case Study Prerequisites

Video 1: Problem_Statement

Submit your work on quora case study

Video 2: Basic EDA and Feature Engineering

Video 3: Quora - Text Preprocessing and Advanced Feature Engineering

Video 4: Quora - Text Preprocessing and Advanced Features Analysis

Video 5 :Quora - Weighted Word Vectors

Video 6: Quora ML Models

Seoul Bike Trip Duration Prediction

Dataset and Instructions for seoul

Seoul Bike - Problem Statement and EDA

Seoul Bike - Modeling

Newyork Taxi Demand Prediction

Dataset & Instructions for nytaxi

V1 : Instructions

V2 : Achieving the objective

V3 : Understanding the data

V4 : Dask dataframe

V5 : Understanding the features

V6 : Performance matrix

V7 : Latitude & Longitude

V8 : Data cleaning

V9 : Removing outliers

V10 : Data preparation part 1

V11 : Data preparation part 2

V12 : Data preparation part 3

V13 : Data preparation part 4

V14 : Data preparation part 5

V15 : FFT

V16 : SMA

V17 : WMA

V18 : EMA

V19 : Regression models

V20: Complete Summary

Credit Risk Analysis Case Study

Credit Risk Case Study Introduction

Crdit Risk Assignment

Data Preprocessing Part - 1

Data Preprocessing Part - 2

Data Preprocessing Part - 3

Model Building

Expected Loss Explanation

Expected Loss Assignment

Expected Loss Calculation

Fecebook Case Study

Video 1: Problem Statement Explanation

Video 2 : Graph Introduction

Video 3 : Dataset Format

Project Submission(Facebook)

Video 4 : Mapping to Supervised Learning Problem

Video 5 : Basic EDA

Video 6 : EDA Part 2(Followers_And_Following_Stats)

Video 7 : Posing The Problem Into Classification Task

Video 8 : Feature Engineering Jaccard and Cosine

Video 9 : Feature Engineering PageRank & Shortest Path

Video 10 : Feature Engineering Connected Components

Video 11 : Feature Engineering Adar Index

Video 12 : Feature Engineering Katz Centrality

Video 13 : Feature Engineering HUBS Score

Video 14 : Feature Engineering SVD & Weighted Features

Video 15 : Modeling

Maths And Stats For Data Science

Linear Algebra Tutorials

Video 1- Introduction of Vectors

Video 2-Addition and Subtraction of vectors

Video 3-Properties & Co-ordinate system

Video 4-Vector Sum

Video 5-Dot Product

Video 6- Examples

Video 7- Arithmectic operations on Vectors

Video 8- Vector Norms

Video 9-Changing Coordinates

Video 10- Linearly Independent vectors

Video 11-Basis Vectors

Video 12-Matrices Introduction

Video 13-Types and Properties of Matrices

Video 14- Rank

Video 15- Nullity and Null Space

Video 16-Linear Equations case 1

Video 17- Case 2

Video 18- Case 3

Video 19 - Vectors Revisited

Video 20- Vector line equation and projection

Video 21- Hyperplanes & halfspaces

Video 22- Eigenvalues & Eigenvectors

Video 23-Properties of eigenvectors

Calculus Tutorials

Video 1-Functions

Video 2-Derivatives

Video 3-Derivative 2

Video 4-Continous function

Video 5- Integration

Video 6-Maxima and Minima

Video 7- Gradient Descent

Statistics Tutorials

Video 1- Mean, Median, Mode

Video 2-Population and Sample mean

Video 3-Population Variance

Video 4-Sample Variance

Video 5-Standarad Deviation

Video 6-Alternative formula for variance

Video 7- Probability

Video 8-Types of Events

Video 9- Example of events

Video 10-Conditional Probabilty

Video 11-Marginal & Conditional Probability

Video 12-Random Variable

Video 13-Probabilty Distribution

Video 14-Normal Distribution

Video 15-Example 1 of Normal distribution

Video 16-Example 2 of Normal Distribution

Video 17-Binomial Distribution

Video 18-Example of Binomial Distribution

Video 19- Poisson Distribution

Video 20-Example of Poisson Distribution

Video 21-Central Limit Theorem

Video 22- Hypothesis

Video 23-Null & Alternate Hypothesis

Video 24-Terms related to Hypothesis Testing

Video 25- Example 1

Video 26- Recap of Example 1

Video 27- Example 2

Video 28- Z test

Video 29-T test

Video 30- Degrees of Freedom

Video 31-1 sample t test

Video 32- Two sample T test

Video 33- Paired T-test

Video 34- Chi-Sqare test1

Video 35-Chi Square test2

Video 36-ANOVA introduction

Video 37- Sum of Squares

Video 38- Sum of squares within and between

Video 39- Types of ANOVA

Video 40- Skewness & Kurtosis

Linear Algebra Assignments

Download Dot Product Assignment

Video 1 : Dot Product(Theory )

Video 2 : Dot Product(Coding )

Dot Product solution video

Download Norm of Vector Assignment

Video 3 : Norm(Theory)

Video 4 : Norm(Coding)

Norm solution video

Download Linear Combination Assignment

Matrix Mult Assignment Video

Linear comb solution video

Download Matrix Multiplication Assignment

Matrix Mult solution video

Download Linear equation system Assignment

Video 6: Matrix Equation

Video 7 : Linear Equation

Lineareqn solution video

Download Linear transformation Assignment

Video 8: Linear Transform

Linear transform solution video

Download Eigenvalues and Eigenvectors Assignment

Video 9 : Eigvector and Eigenvalues

Eigenvalues and Eigenvectors Solution Video

Vector Spaces Assignment

vector spaces solution

Video 1: Dot Product And Angle Between Them

Video 2 : orthogonal, cross product and linear combination

Video 3 : Singular Value Decomposition

vector solution

Statistics Assignment

Download Data Analysis Assignment

data analysis solution

Download Central Tendency Assignment

central tendency solution

Concept of Quantiles

concept of quantile solution

Variability

variability solution

Housing case study

housing solution

Mobile phone case study

mobile solution

Sampling

sampling sol video

T-test

T-test-solution

A/B Testing

AB solution

Drug Assignment

drug solution

Payroll Assignment

payroll solution

Stats behind plots

stat behind plot solution

probability in data science

probability in data science solution

SQL

SQL Crash Course(Add on)

Database concept

Mysql installation

SQL Queries Basic + Intermediate

SQL Basics

Video 1: CRUD

Video 2: Data Definition Language

CRUD Operations

crud solution

SQL Intermediate

Video-3 Limit, Orderby

Video-4 Where,Distinct,ComparisonOperators

Video-5 Logical_Operators

Video-6 Groupby,Having

Group by

group by solution

Video 7: Joins

Joins Queries

Joins solution

VIdeo-8 Nested_Queries

Subquery

subquery solution video

Video 10: Table constraints

Table Constraints

table constraint solution video

Video 11: case when statements

PGexercise Problems

PGexercise Solution

Hackerank SQL Problems

Hackerank SQL Solution

Company Schema Practice Problem

Company Schema solution video

Advanced SQL

University schema Case Study

university schema solution

Cursors_tutorial

Cursors Assignment

Cursors solution video

SQL_Views tutorial

Views Assignment

Views solution

Transactions tutorial

Transactions Assignment

transactions solution video

Window functions

CTE Tutorial

SQL String transformations & Regex

Date Time Manipulation

Introduction of Data Modeling +forward engineering

SQL Reverse engineering

stored procedures

Case Study 1 : DATAMART

Case Study 2 : DATA BANK

Case Study 3: Texture Tales

Neural Networks & Computer Vision

Neural Network Videos

1-DL intro

2-ANN

3-Into Perceptron

4-Perceptron & weigths & biases

4.1-notebook In Kaggle

5-Coding Perceptron-1

6-Perceptron learning_2

7-Perceptron learning animation_3

8-MLP

9-Activation Function_Sigmoid

10-More Activation Functions

11-Some more sctivation functions

12-important theory on activation function

13-Loss in Regression

14-Loss in Classification

15-keras framework

16-important keras modules

17-solving binary classification problem using MLP

18-solving multi classClassification problem using MLP

19-solving regression problem using MLP

20-using different optimizers

21-evaluationg results of different optimizers

22-Into CNN's

23-Into CNN-1

24-CNN-2

25-CNN-3-extended

26-CNN-4-extended

27-CNN-5-final

Neural Network Assignments

TensorFlow Fundamental

Building Blocks of Neural Network

Activation Functions in Neural Network

Forward and Backward Propagation

Training Neural Network

Loss Function

Optimizers & Types of Gradient

Regularization Techniques

Python Oops

Neural Network From Scratch

PyTorch Fundamentals(Optional)

Computer Vision Videos

1-Image_Basics(openCv)

2-Pixels_work

3-draw-to-understand-coordinated

4-manipulating_pixels

5-Image_channels

Computer Vision Assignment

CNN Introduction Tutorial

Introduction to CNN

Image Preprocessing Tutorial

Image Data Pre-Processing

Fit Generator Tutorial

CNN With Fit Generators

Transfer Learning Tutorial

Transfer Learning

AlexNet Tutorial

AlexNet

VGG16 Tutorial

VGG-16

Erosion and Dilation

Face Detection Pet Project

OpenCV

YOLO Tutorial

Image_Segmentation Tutorial

Image Segmentation

DeOldify Tutorial

GAN Tutorial

NLP

1.1 : tokenization

1.2 : lemmatization

1.3 : stemming

1.4 : stopwords

1;5 : stopword_notebookproblem

Basics of NLP

1.6 : Basics NLP Explanation Video

2.1 : BOW

2.2 : countvectorizer

2.3 : tf-idf

2.4 : ngrams

2.5 : pos

Converting Words into vectors (Basics)

2.6 : Converting Words into Vectors Explanation Video

3.1-wordembedding

3.2 : gensim

3.3 : word2vec

Converting Words Into Vectors (Advanced)

3.4 : Converting Words into Vectors Advanced Explanation Video

4.1 : Introduction To Sentimental Analysis

Sentiment Analysis

4.2 : Sentiment Analysis Explanation Video

5.1 : AF

5.2 : sigmoid

5.3 : tanh

5.4 : RELU

5.5 : softmax

5.6 : ann

ANN

5.7 : ANN Explanation Video

6.1 : RNN

6.2 : Types_of_RNN

6.3 : practical_example_on_rnn

RNN

6.4-RNN_Assign_Explanation

7.1 : RNN_LIMITATION

7.2 : LSTM

LSTM

7.3-LSTM_Assign_Explanation

8.1 : GRU

8.2 : BILSTM

GRU & Bidirectional LSTM

8.3-GRU_LSTM_Assign_Explanation

9.1 : Transformers

Encoder, Decoder & Transformer

9.2-Transformer_Assign_Explanation

10.1 : BERT

10.2 : Bert-Tokeniser

Bert

10.3_Bert_Assign_Explanation

11.1-Topic Modelling

11.2-Topic Modelling Implementation

Autocorrect

12-Autocorrect Explanation

Time Series

timeseries files+dataset link

Video 1- Introduction to time series

Video 2 - Time Series Decomposition

Video 3- Simple Models for Time Series

Video 4- Simple Exponential Smoothing

Video 5- Holt_s Method

Video 6- Stationarity and Lag

Video 7- Covariance _ Correlation

Video 8 - Unit Test _ ADF Test

Video 9- Differencing of Time Series

Video 10 -ACF _ PACF

Video 11- ARIMA

Video 12- SARIMA

Video 13- SARIMAX

Video 14- ANN

Video 15- CNN

Video 16- LSTM

Introduction To Time Series

Introduction To Time Series Explanation Video

STATIONARITY

STATIONARITY Explanation Video

ACF & PACF

ACF & PACF Explanation Video

ARIMA

ARIMA Explanation Video

Auto ARIMA, SARIMA & SARIMAX

Auto ARIMA, SARIMA & SARIMAX Explanation Video

Model Selection

Model Selection Explanation Video

VARMA

Autoregressive ML Models

Autoregressive Explanation Video

ANN for Time Series Forecasting

CNN For Time Series Forecasting

LSTM For Time Series Forecasting

Deep Learning Projects

Dog-Cat Classification Project

VIRUS MNIST

Humpback Whale Identification

Sound Classification

Anime Face Generation using GAN

Language Translation Using Transformer

Email Classification Using Bert

Text Generation with RNN

Anime Recommender System

Product Recommender Based On Sentiment Analysis

Retail Sales Prediction

Chatbot

Human Activity Recognition

Video 1 : HAR Problem Statement

Video 2 : Dataset Description(HAR)

Project Submission(HAR)

Video 3 : HAR Dataset Loading

Video 4 : HAR Dataset Cleaning

Video 5 : Exploratory Data Analysis HAR

Video 6 : Segmentation using t-sne

Video 7 : HAR Classical ML Approach

Video 8 : HAR Using LSTM

Flower Classification

Video 1 : Flower Classification Problem Explanation

Project File And Submission For Flower Classification

Video 2 : Flower Classification Using CNN

Project File And Submission For Resnet

Video 3 : Flower Classification Using Resnet

Video 4 : Deploying Resnet Using GRADIO

Preview - Data Science Combo Course