This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price

70+ DataCamp Course Notes, Projects, Codes, Exercises on Python, R and SQL with full DS & ML Certification,

a tool for comparing the predictions of any text classifiers

This Repository contains the real life use cases of GenAI (LLM+RAG) in Finance Domain. I covers many projects use cases with theory and projects.

Ethereum Fraud Detection Models

Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.

This Repo contains tools that allow us to import, clean, manipulate, and visualize data —Includes Python libraries, like pandas, NumPy, Matplotlib, and many more to work with real-world datasets to learn the statistical and machine learning techniques.

Data science, machine learning books and resources

Demonstrating the efficiency of pmdarima’s auto_arima() function compared to implementing a traditional ARIMA model.

Все о машинном обучении и не только...

A credit scoring web app based on an ML model trained on relevant data.

Data Career Handbook for all

A list of Incomplete Interview Questions (Python and Data Science only )

The dataset builder script extracts the most relevant market data straight from Binance's API and builds a series of datasets that can be used in data science and machine learning projects.

This repository contains the implementation of the research paper tVelloso, E., Bulling, A., Gellersen, H., Ugulino, W. and Fuks, H., 2013, March. Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference (pp. 116-123).

The dataset having Pneumonia and Normal chest X-Ray images were trained on different numbers of epochs to check the variability in the training and validation accuracies. The ResNet50 model with the highest and closest Training and Validation accuracies was then used for the prediction.

Predicting the incidents raised by the customer

mltrons dptron: Dirty Data in, Clean Data Out!

This project uses supervised machine learning techniques with multiple regression models to predict CO2 emissions in Canada, it includes data cleaning, encoding, analyzing and visualization to identify patterns, resulting in a model that can make accurate predictions.