Data Preprocessing in Python
Learn to transform raw text into structured lists and CSVs using Python, enhancing data organization and analysis skills for practical applications.
Step-by-Step Machine Learning Project Implementation: EDA, Feature Engineering, Selection, and Model Training
Comprehensive guide to implementing a machine learning project, covering data cleaning, EDA, feature engineering, selection, model training, and hyperparameter tuning.
Send E-mails From Low-Code Python Apps
Learn to build a web app for sending bulk emails using WindmillDev and Brevo's REST API. Covers Python coding, Windmill UI creation, and API integration for efficient email automation.
The Future of Crypto - Breaking New Ground in Emerging Markets
Explore cryptocurrency adoption in emerging markets, focusing on Dash's efforts to provide financial solutions for the unbanked and facilitate daily transactions.
Interactive Brokers API and TradingView Charts in Python
Learn to integrate TradingView Lightweight Charts with Interactive Brokers API in Python. Build projects for data visualization, real-time updates, and automated trading with hands-on coding examples.
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.
Python Data Science Day: Comprehensive Workshop on Data Analysis and AI Technologies
Explore cutting-edge Python data science topics with expert-led sessions on AI, machine learning, data analysis, and innovative tools. Gain practical insights and hands-on experience in this comprehensive event.
The Dynamic Mode Decomposition - A Data-Driven Algorithm for Complex Systems Analysis
Explore the Dynamic Mode Decomposition algorithm for analyzing complex systems, including its theory, applications, and implementation using PyDMD package in Python.
Data Analytics and Generative AI
Explore how generative AI revolutionizes data analytics, streamlining tasks, transforming workflows, and ensuring ethical practices. Gain practical insights and real-world applications for data professionals.
Data Analytics and Generative AI: Streamlining Tasks and Transforming the Workforce
Explore how generative AI revolutionizes data analytics, streamlines tasks, and transforms the workforce. Learn practical applications using Python and Power BI with real-world examples.
Let's Play with Charmed Spark - Apache Spark on Kubernetes
Explore Apache Spark on Kubernetes using Charmed Spark. Learn to deploy, configure, and run Spark workloads, integrate with Kafka, and monitor jobs through hands-on demonstrations.
Julia for Python Programmers
Hands-on introduction to Julia for scientific computing and data science, focusing on its efficiency and interactive capabilities for technical applications and scalable computing.
Streamlining Data Preparation with Pydantic - A 25-Minute Guide
Explore Pydantic's power in data validation and cleaning for Python projects. Learn to ensure consistency, handle missing values, and streamline data preparation in just 25 minutes.
Exploring Data Wrangler in VS Code - Python Data Science
Discover Data Wrangler in VS Code: Efficiently explore, analyze, and clean Airbnb listings data. Learn to invoke and use this powerful tool for streamlined data preprocessing in Python notebooks.
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.
Breaking Data Silos with Semantic Link in Microsoft Fabric
Explore Semantic Link in Microsoft Fabric to break data silos, enabling seamless collaboration between data scientists and analysts for creating insightful solutions and leveraging semantic information.
Simplifying Data Analysis and Visualization with Developer Tools and AI
Explore data analysis and visualization using AI-assisted tools. Learn to leverage GitHub, Jupyter, Copilot, and LIDA for efficient insights and visualizations, even without extensive Python experience.
Solving Real-World Data Science Problems with LLMs - Historical Document Analysis
Learn to analyze historical documents using Python and LLMs. Covers entity parsing, document connection, and data insights extraction. Practical application with Freedmen's Bureau dataset and both closed and open-source LLMs.
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.
Tech Recruiting Academy - How to Recruit a Python Developer
Learn effective strategies for identifying, attracting, and evaluating Python developers. Gain insights into the Python ecosystem and essential skills for successful tech recruitment.
TDA for Chromatic Point Clouds
Generalizace persistentní homologie pro barevné bodové mraky. Detekce prostorových interakcí mezi různými typy bodů s aplikacemi v biologii a medicíně.