Diffprivlib - Privacy-Preserving Machine Learning with Scikit-Learn
Explore differential privacy in machine learning using Diffprivlib, a tool for training accurate models with robust privacy guarantees, seamlessly integrating with scikit-learn and numpy.
Boosting Simulation Performance with Python
Explore discrete-event simulation for robotics, boosting performance and determinism. Learn to overcome challenges in event-driven systems and distributed simulations for faster development and testing cycles.
Decision Science with Probabilistic Programming
Explore generative models and probabilistic programming for decision-making under uncertainty, integrating with robust optimization techniques to enhance business strategies.
Real Time Stream Processing for Machine Learning at Massive Scale
Practical insights on building scalable data streaming ML pipelines for real-time processing using Python, Kafka, SpaCy, and Seldon. Covers key concepts and best practices through a Reddit comment moderation case study.
Simulation of Logistic Systems in Python with Salabim
Explore discrete event simulation for logistics using salabim, an open-source Python package. Learn to model complex systems with advanced animation and statistical features.
Deceptive Security Using Python
Explore deceptive security techniques using Python, including WebTrap and DemonHunter tools. Learn how to implement machine learning for XPath injection attack mitigation in web services.
Object Internals
Explore Python's object internals, memory management, and data structure behavior. Gain insights into mutability, copying, sorting, and memory allocation for improved code understanding and optimization.
Machine Learning for Everyone
Discover the essentials of machine learning, neural networks, and reinforcement learning in this engaging talk. Gain practical insights and witness a mind-blowing demo to kickstart your ML journey.
Painting with GANs - Challenges and Technicalities of Neural Style Transfer
Explore Neural Style Transfer using GANs, including challenges, technicalities, and applications in gaming, fashion, and mobile apps. Learn about loss functions and see code examples.
Writing Extensions and Bindings for GPU Made Easy
Learn to optimize deep learning computations by writing custom C and CUDA extensions for GPU, with a focus on image search across billions of items and seamless integration with Python codebases.
Ray - A System for High-performance, Distributed Python Applications
Ray: open-source framework for scaling Python applications from laptop to cluster, solving performance challenges in ML/AI systems. Learn its features, use cases, and how it compares to alternatives.
NLPeasy - A Workflow to Analyse, Enrich, and Explore Textual Data
Discover NLPeasy: a streamlined workflow for analyzing, enriching, and exploring textual data using pre-trained models, Docker, and Jupyter Notebooks. Simplify your NLP projects with this powerful Python package.
The Painless Route in Python to Fast and Scalable Machine Learning
Learn to optimize Python for high-performance machine learning, from Intel-enhanced packages to scalable data processing and analytics pipelines that rival C++/MPI performance on large datasets and clusters.
Can We Deploy Yet?
Prepare your Python project for production deployment with essential checklist, Docker image optimization, environment differences, and real-world strategies for handling exceptions, logs, and metrics.
Automating Machine Learning Workflow with DVC
Discover how to automate and streamline machine learning workflows using DVC, from data ingestion to model deployment. Learn to organize pipelines efficiently, regardless of project size.
Mastering a Data Pipeline with Python - 6 Years of Learned Lessons from Mistakes
Explore key insights and best practices for building robust data pipelines with Python, covering data acquisition, transformation, storage, and workflow management based on 6 years of experience.
How to Be Pythonic - Design a Query Language in Python
Explore the design of WOQLpy, a Python query language for TerminusDB. Learn about challenges, methods, and best practices in creating Pythonic packages, with interactive discussions on effective Python design.
Sharing Reproducible Python Environments with Binder
Learn to share reproducible Python environments using Binder, integrating Jupyter Notebooks and Docker for easy packaging and cloud-based sharing of data science projects without complex setup.
Running Unit Test on Top of Serverless Service
Explore serverless architecture for unit testing, including parallelization approaches, implementation insights, and cost-benefit analysis for improved developer productivity.
Developing a Match-Making Algorithm Between Customers and Go-Jek Products
Explore how GoJek developed a personalized recommendation system using PySpark to match customers with relevant products and vouchers, improving conversion rates.
The Hidden Power of the Python Runtime
Explore Python's hidden runtime events, frame objects, and powerful tools for inspecting program state during execution, enhancing your programming skills and debugging capabilities.