Demystifying Deep Learning for Data Scientists
Uncover the inner workings of deep learning frameworks and gain foundational knowledge to confidently implement models in any framework of your choice.
Small Big Data - Using NumPy and Pandas When Your Data Doesn't Fit in Memory
Techniques for processing data too big for memory but too small for Big Data clusters, using NumPy and Pandas: compression, batching, and indexing for efficient data handling.
Record Deduplication with Python
Aprenda técnicas de deduplicação de registros em Python para identificar duplicatas em conjuntos de dados sem identificadores únicos, aplicável em governos e empresas.
It's Officially Legal so Let's Scrape the Web
Learn Python web scraping techniques to automatically collect data from websites, covering HTML basics to advanced pipeline methods for dataset compilation.
Easy Data Processing With Azure Fun
Learn to process data efficiently using Azure Functions and Python, exploring serverless computing, best practices, and practical use cases for scalable cloud applications.
Effective Data Visualization
Learn advanced data visualization techniques using Python libraries to effectively communicate complex data across various fields, from choosing plots to aesthetic decisions.
Python in High Energy Physics
Explore Python's growing role in High Energy Physics, from its adoption and key libraries to its impact on data analysis and machine learning in particle physics research.
Building Interactive Applications for Image Data
Interactive Python tools for image processing, combining Dash for web apps and scikit-image for advanced algorithms. Explore, annotate, and analyze scientific and business images efficiently.
How to Build an Intelligent Indoor Garden
Learn to create an automated indoor garden system using sensors, microcontrollers, and CircuitPython. Explore web app development, Raspberry Pi setup, and IoT data analysis for plant care automation.
Docker and Python - Making Them Play Nicely and Securely for Data Science and ML
Docker best practices for data science and machine learning: optimizing image builds, ensuring security, and implementing efficient deployment workflows for data-intensive applications.
Decoding Bias and Narrative in Competitive Video Games
Explore video analysis of Overwatch eSports broadcasts to uncover biases and narratives in competitive gaming, examining player focus and storytelling techniques.
Geospatial Public Policy Analysis with GeoPandas
Analyze US higher education institutions using GeoPandas, exploring education deserts and equity implications through hands-on data analysis with NCES and IPEDS datasets.
Datos, Python y Humanos
Explorando retos y oportunidades de la ciencia de datos en Latinoamérica: historias reales, obstáculos comunes y visión de futuro para científicos de datos y empresas en la región.
Education Summit - Bringing Coding Literacy Through Python
Educators discuss innovative approaches to teaching Python, including critical data science, context-based learning, and principles-driven development, to enhance coding literacy for diverse audiences.
Extending the Python Ecosystem to Xilinx
Explore PYNQ: Python-based platform integrating microprocessors, microcontrollers, and FPGAs. Learn to leverage programmable system-on-chips for embedded development using familiar Python ecosystem and Jupyter notebooks.
Bridging Data Science and Data Infrastructure with Apache Airflow
Explore how Apache Airflow bridges data science and infrastructure, enabling collaboration between teams and facilitating the development of flexible, observable, and resilient data pipelines.
Polyglot Data with Python - Introducing Pandas and Apache Arrow
Explore polyglot data handling with Python using Pandas and Apache Arrow for efficient data exchange between ecosystems, improving performance and reducing file sizes.
Deploying Python at Scale with Dask
Explore scaling Python with Dask on distributed systems, focusing on deployment challenges and solutions for cluster resource managers like Kubernetes, Yarn, and cloud platforms.
Migration from Python 2 to 3
Learn strategies for migrating Python 2 code to Python 3, focusing on writing single-source programs compatible with both versions using python-future. Gain practical skills for a smooth transition.
GPU-Accelerated Data Analytics in Python
Explore GPU-accelerated data analytics using RAPIDS libraries in Python. Learn ETL, machine learning, graph analytics, and more with familiar APIs for faster computation and model iteration.
Time for Time Series
Explore time series analysis fundamentals, decomposition techniques, and forecasting models using Pandas. Learn to extract insights and create powerful predictions from temporal data.