Implementation scripts of Machine Learning algorithms on Scikit-learn and Keras for complete novice..

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.

Linear Regression Feature Selection and Trainer

Classify pictures by architectural style and recognize objects with CNNs and YOLO

𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐭𝐡𝐞 𝐊 𝐅𝐨𝐥𝐝 𝐂𝐫𝐨𝐬𝐬 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐑𝐅𝐌 𝐚𝐧𝐝 𝐑𝐅𝐌𝐓𝐂 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 𝐮𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐁𝐥𝐨𝐨𝐝 𝐓𝐫𝐚𝐧𝐬𝐟𝐮𝐬𝐢𝐨𝐧 𝐝𝐚𝐭𝐚 𝐬𝐞𝐭 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐂𝐃𝐍𝐎𝐖 𝐭𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐝𝐚𝐭𝐚 𝐬𝐞𝐭 𝐢𝐧 𝐑.

Machine Learning algorithms built from scratch for AMMI Machine Learning course

Optimizing-Hyperparameters-Using-Grid-Search-Deep-Learning

Machine learning: Practical applications

Data sampling library

Data sampling library

Collection of RNN GAN SNN CNN in Tensorflow

An Artificial Neural Network with weight decay created using python using the Numpy library which can read handwritten digits. Uses K-Folds cross validation for training the Neural Network.

An activity recognizer using a neural network implemented from scratch

Bangla Music Mood Detect Pattern Lab Project

Repository for the Brainhack School 2020 team working with fMRI and ABIDE data to train machine learning models.

Progetto di Intelligenza artificiale sugli alberi di decisione con valori mancanti.

This is a universitary project for the exam of software quality and metrics

A Python script that implements Machine Learning Algorithm to predict if a female is affected by Breast Cancer after considering a certain set of features. The credit of the Dataset goes to UCI Repository of ML.

Contains all my data science projects.

WiDS Datathon 2020 on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative.

Comparing Logistic regression, Support vector machine, Decision tree, Random forest and Gradient Boosting models for binary classification ML problem.

Codes and templates for ML algorithms created, modified and optimized in Python and R.

Linear Regression Feature Selection and Trainer

PCA applied on images and Naive Bayes Classifier to classify them. Validation, cross validation and grid search with multi class SVM

[College Course] - Course: BITS F312 Neural Network and Fuzzy Logic

ML model for stock trend prediction using Python

Predicted the survival of the Titanic passengers using Machine Learning Algorithms (Kaggle Challenge)

Imagine you are the front runner for democratic party primaries in 2008 - 1 week into elections you have won a few states(Obama) and your opponent (Hillary) is catching up. How you can use analytics to predict which of the remaining seats will you win using demographic data from states you won and lost. Can we accurately classify win or lose for the remaining seats using data. Can we use this prediction to find out factors which impact our chances of winning and improve our appeal to places that are predicted loss thus improving our chances of winning? Well , Let's find out!

Employed hyper-parameter tuning (Gridsearch CV) and ensemble methods (Voting Classifier) to combine the results of the best models. Data Cleaning and Exploration using Pandas. Stratified Cross Validation to model and validate the training data