Foursteps Solutions

Basic Plotting

Loading External Data and Understanding

Visualization - Bi Variant Analysis

Visualization - Uni Variant Analysis

Visualization - Multi Variant Analysis

Data Cleaning - 1

Data Cleaning - 2

Theory - Introduction and Measure of Association

Theory - Co-Variance and Correlation

Theory - Residual and MSE

P1-Hands On - Car Price prediction

Hands On - Fine tuning model

Theory - Introduction to Classification

Theory - Decision Trees

P2 - Hands on - Decision Tree Implementation and Fine tuning

Accuracy Metrics - Precision, Recall, F1 Score

Decision Tree - Feature Splits

Theory - Random Forest

P3 - Hands on - Random Forest Implementation and Fine tuning

Theory - K Nearest Neighbors

P4 - Hands on - KNN Implementation and Fine tuning

Theory - Support Vector Machines

P5 - Hands on - SVM Implementation and Fine tuning

Theory - Logistic Regression

P6 - Hands on - Logistic Regression Implementation and Fine tuning

Theory - Gaussian Naïve Bayes

P7 - Hands on - GNB Implementation and Fine tuning

Hello World

Drawing Operations

Basic Image Handling

Masking

Smoothing and Blurring

Thresholding

P8 - Contours and License Plate Detection

Feature Extraction and Challenges Faced

P9 - Haralick Textures

P10 - Multi - Feature Extraction - Sign Board Classification

P11 - Face Detection - Haar Cascade Classifier

P12 - Local Binary Pattern Histogram - Face Recognition

P13 - Histograms of Oriented Gradients

Assignment - Handwritten character Recognition

Assignment - Face Emotion Recognition System

Assignment - Numerical Data Classification

Theory - Introduction to Clustering

Theory - K Means and DB clustering

P14 - Hands on - Kmeans Clustering

Hands on - DB Scan

Assignment - MNIST Clustering

Introduction to Neural Networks

Neuron, Layers, Activation Functions

Forward and Back Propagation

Gradient Optimization and weight updation

P15 - Hands on - Multi Layer Perceptron for numerical data

Hands on - Model Fine tuning

P16 - Categorical Data and K Fold Validation

P17 - Hands on - MLP for Images

Hands on - Model Analysis and saving

Introduction to CNN

Convolution and Pooling Layers

P18 - CNN_Implementation

P19 - Car Classification using CNN with Callbacks

Transfer learning

P20 - Transfer Learning implementation

Assignment - Classification with localization

Assignment - Plant Disease Classification

Introduction to Object detection

Introduction to Yolo Architecture

P21 - Implementing Yolo Architecture and model training

Model Inference

Introduction to GAN

Assignment - Custom Object Detection for helmet detection