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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

ai-for-medicine-specialization-deeplearning.ai

Contains detailed notes, codes, answers to quizzes and exercises of all the 3 courses of the AI for Medicine specialization, by deeplearning.ai

amazing-feature-engineering

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

consumer-credit-card-prediction

The regression problem to understand the consumption pattern for credit cards at an individual consumer level and predict the average spend of customers for the next 3 months.

extracting-business-insights

Finding business insights

fifa-project

FIFA Project

ga-code-alongs

ga-learner-dst-repo

hackathon-projects

This repo contains notebooks for all the hackathon

hirenhk15.github.io

housing-price-prediction

This is regression problem to predict median house values in Californian districts, given a number of features from these districts. The California Housing Prices dataset from the StatLib repository. This dataset is based on data from the 1990 California census.

review-sentiment-prediction

Review Sentiment Analysis

risk-models-for-medical-prognosis

An End-to-end Machine Learning System with User Interface for predicting the 10-year risk of death of individuals from the NHANES I epidemiology dataset. This project leverages risk models (a.k.a. prognostic models) built using machine learning to perform predictions given the patient's medical profile.

steadymark

use your python snippets from your README.md as regression tests

tools-to-design-or-visualize-architecture-of-neural-network

Tools to Design or Visualize Architecture of Neural Network

uci-appliances-energy-prediction

Experimental data used to create regression models of appliances energy use in a low energy building.

vehicle-loan-default-prediction

Financial institutions incur significant losses due to the default of vehicle loans. This has led to the tightening up of vehicle loan underwriting and increased vehicle loan rejection rates. The need for a better credit risk scoring model is also raised by these institutions. This warrants a study to estimate the determinants of vehicle loan default. The Machine Learning approach allows to predict vehicle loan defaults.