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500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

catsvsdogsclassification

competitive-programming

datetodaysmaker

Converts Date to ithDay of year

dsa-bootcamp-java

This repository consists of the code samples, assignments, and the curriculum for the Community Classroom complete Data Structures & Algorithms Java bootcamp.

face-detection-using-open-cv

This is a simple demonstration of face detection using the OpenCV library in python (in a few lines of code). Face detection using Haar cascades is a machine learning based approach where a cascade function is trained with a set of input data. OpenCV already contains many pre-trained classifiers for face, eyes, smiles, etc.. We will be using the face classifier.

face-recognition-on-olivetti-dataset

In this study, face recognition was performed using the face images in the Olivetti data set. Principal components of face images were obtained by PCA. According to three different classification models, accuracy score obtained. Parameter optimization of the best model has been made

fastbook

The fastai book, published as Jupyter Notebooks

first-contributions

🚀✨ Help beginners to contribute to open source projects

flight-price-prediction-with-deployment

I have built a simple web app that predicts the price of flights based on inputs such as Departure date and time, Source and destination, etc. The model is trained on "Random Forest Regressor" and deployed using "Streamlit" on Heroku. The accuracy of the model was found out to be 95% on the train data and about 80% on the test data.

frescoplay

githubgraduation-2021

Join the GitHub Graduation Yearbook and "walk the stage" on June 5.

googlekeepclone

A clone of Google Keep with its original Material Design aesthetics

hemshree

heroku-demo

image-classification-using-cnn-in-pytorch

The aim of this project is to predict the label of the object given the image data using Convolutional Neural Networks(CNN) in Pytorch. The dataset used is CIFAR-10 dataset which is a subset of the 80 million tiny images dataset and consists of 60,000 32x32 color images containing one of 10 object classes, with 6000 images per class.

mathinspector

A visual programing environment for scientific computing with python

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

ml_projects

monai

AI Toolkit for Healthcare Imaging

newsfinder

novid-20

An amazing PWA which is a solution to foretell the likelihood of being in vicinity of COVID-19

polynomial-regression

Data analysis and visualization on Polynomial Regression using EA Sports FIFA 19 player roster database.

py

Repository to store sample python programs for python learning

pytorch-deep-learning

Deep Learning (with PyTorch)

reducingmarketwaste_hackerearthcompetition

Problem Statement: The company has products that can be used for hiring assessments. The task is to predict the probability percentage that a client will purchase a product from the features provided in the dataset.

sarthakkmishraa

sentiment-analysis-using-twitter-api

The objective of this program is to analyse Donald Trump's tweets and classify the sentiment as either positive, negative or neutral. I have used the Twitter API to fetch the tweets and TextBlob library for performing the NLP task. It includes tokenisation, removing special character and irrelevant nouns and pronouns(stopwords) and passing the tokens to the sentiment classifer which assigns the tweets polarity of positive, negative and neutral by the values 1, -1 and 0 respectively.

stock_market_prediction

The aim of this project is to analyse the stock market data and predict the stock closing price using Long Short Term Memory(LSTM ) deep learning algorithm and evaluate the accuracy of the model. Also, the trained data is used to predict the stock closing prices for the next 30 days in future.