#Datascience-machinelearning
Showing 6 of 6 repositories tagged #datascience-machinelearning, ranked by stars
Data science for beginners involves learning to extract insights from data using statistics, programming (Python/R), and visualization. Key steps include data collection, cleaning, analysis, modeling, and communicating findings. Beginners should start with Python, basic math (linear algebra/calculus), and build projects to create a portfolio.
Data science, machine learning books and resources
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.
70+ DataCamp Course Notes, Projects, Codes, Exercises on Python, R and SQL with full DS & ML Certification,
This project analyzes and visualizes the Used Car Prices from the Automobile dataset in order to predict the most probable car price
Data Career Handbook for all