Linear Regressions with StatsModels - Data Science Tutorial
Learn to create linear regressions using StatsModels, exploring datasets and examples with NumPy, Pandas, Matplotlib, and Seaborn. Analyze professor ratings and tipping strategies through practical applications.
Exploratory Data Analysis with Binance API Using Python and Pandas - MLTrader Episode 1
Learn to extract and analyze real-time crypto data from Binance using Python and Pandas. Covers API setup, data pulling, exploratory analysis, and candlestick visualization with MPLFinance.
Pandas for Data Science - Python Crash Course
Learn essential Pandas skills for data science quickly. Create, update, visualize, and preprocess data frames from various sources, then output to CSV, JSON, and HTML formats.
PyScript Tutorial: Machine Learning with Scikit-Learn - Training and Interactive Prediction
Create interactive machine learning app with PyScript: upload CSV, train models, and make predictions using Pandas, Panel, and Scikit-Learn.
How to Become a Practical Data Scientist with Kaggle Learn
Discover a comprehensive, free path to becoming a practical data scientist using Kaggle Learn's step-by-step courses, covering Python, machine learning, data visualization, and more.
Effortless Data Analysis and Cleaning with Data Wrangler in VS Code
Explore Data Wrangler in VS Code: Boost productivity with code-centric data cleaning, automated Pandas code generation, and insightful visualizations for efficient data analysis.
Python for Data Science
Comprehensive guide to mastering Numpy, Pandas, and Plotly for data science in Python. Covers core concepts and practical applications with free, commented code files for hands-on learning.
Building Dashboards with PyScript and Altair - Part 1
Learn to build interactive dashboards using PyScript, Altair, and Pandas. Create visually appealing data visualizations from fitness tracker data with step-by-step guidance on data processing and chart customization.
Simplifying Testing of Spark Applications
Learn techniques to simplify testing Spark applications, covering Python UDFs, Pandas UDFs, and functional APIs. Explore practical scenarios and demos for efficient data processing and analysis.
How to Forecast Sales Using Prophet and Python
Learn to build accurate sales forecasts using Prophet and Python in just 15 lines of code. Discover how to leverage this powerful tool for various time series predictions, from market trends to weather forecasting.
Coding Up a Linear Regression Algorithm From Scratch - Build Linear Regression From Python
Advanced Python tutorial on implementing Linear Regression from scratch, covering object-oriented programming, vectorized operations, and efficient coding strategies. Bridges theory and practice for experienced data scientists.
GPU-Acceleration for Pandas, NetworkX, and Apache Spark MLlib - Accelerating Data Science Tools
Discover GPU-accelerated data science tools for pandas, NetworkX, and Apache Spark MLlib. Learn about RAPIDS cuDF, accelerated data processing, and optimizing machine learning pipelines for enhanced performance and accessibility.
Data Science: The Bear Necessities - Exploring Koala Data with Python and Pandas
Explore koala data using Python, Pandas, and Matplotlib to create informative visualizations and gain insights into protecting these endangered Australian icons.
Data Science: Complete Roadmap to Become a Data Scientist
Comprehensive roadmap to becoming a data scientist, covering essential skills, tools, and resources. Includes job prospects, learning strategies, and recommended books for career advancement.
Pandas 2, Dask or Polars? Quickly Tackling Larger Data on a Single Machine
Explore Pandas 2, Dask, and Polars for efficient large data processing on a single machine. Compare features, performance, and ecosystem compatibility to choose the best tool for your research workflow.
Machine Learning with Apache Beam
Explore Apache Beam for distributed data pipelines in machine learning, covering inference, data processing, and training with hands-on demos for parallelizing ML workloads.
Caching for Jupyter Notebooks
Aprenda técnicas de caching para acelerar o desenvolvimento em Jupyter Notebooks, melhorando o fluxo de trabalho e reduzindo o tempo de espera em células dispendiosas.
chDB - The Blazing Fast SQL Engine for Data Science
Explore chDB, a high-performance SQL engine for Python data ecosystem. Leverage its extensive data source support, ANSI SQL compliance, and seamless integration with popular libraries for efficient data analysis.
From Pandas to Production: ELT with dlt
Explore data load tool (dlt) to streamline data science workflows, overcome roadblocks, and transition smoothly from exploration to production. Learn best practices for data handling and managing failures with real-life examples.
Introduction to Machine Learning with Python
Explore machine learning fundamentals using Python, covering key concepts and practical applications in this hands-on workshop led by a field engineer from Domino.
Exploring Datasets with Python and Pandas
Explore datasets using Python and pandas. Learn essential data analysis techniques for scientists, engineers, and analysts working with diverse datasets.