RustGPT: My Journey Using Rust + HMTX for Web Dev
Explore the dynamic world of web development with Rust and HTMX. Follow RustGPT's journey into leveraging Rust's robustness alongside HTMX's declarative interactivity to build a ChatGPT clone. Discover firsthand insights, practical implementations, and tips, unlocking the potential of this powerful duo in crafting seamless, high-performance web experiences.
Bitsletter #10: ML Alerts, Secure Web Cookies & Google's C++ Rival
Effective ML alerting tools, secure cookie practices for web, groundbreaking language model compression techniques, and Carbon a potential C++ contender.
Bitsletter #9: The MLOps Journey, Cookie Management, and AI Research Highlights
Dive into the significance of MLOps for ML engineers, explore data point optimization with RHO-LOSS, supercharge shell scripting with ZX, and stay updated with the latest in AI news!
Bitsletter #8: Enhancing Data Science Workflows & Lightweight Web Development
Dive into enhancing ML experiment velocity, streamline your web app bundle size, explore the CogView2 text-to-image advancements, and get updates from the tech world.
Bitsletter #7: Accelerating ML Training & Diving into Geometry-aware 3D GANs
Uncover techniques for streamlined ML data loading, delve into the world of TypeScript, and meet the efficient 3D GANs! Plus, browser extension building tips!
Bitsletter #6: Achieving Reproducible ML, Web Decoupling, and Hyperbolic Embeddings
Unlock ML project best practices, explore decoupled web development with CMS, and discover the power of Poincare embeddings in hierarchical representation.
Bitsletter #5: ONNX Unleashed, Tackling Web Waterfalls & Vision Transformers
Embrace ONNX's hardware access, enhance web UI via SSR, delve into Vision Transformers' success, and stay updated on PyAutoGUI and recent tech news.
Bitsletter #4: ML Debugging Secrets, Concurrent Promises, and Video Creation with React
Bitsletter #3: Cluster Load Balancing, Incremental Web Updates, & Matrix Magic
Explore balancing ML clusters, utilizing Incremental Static Regeneration for web, and groundbreaking matrix multiplication techniques in this edition.
Bitsletter #2: The Power of Data Centric ML & Web Vital Enhancements
Dive into the benefits of a data-centric approach in ML, web vital metric improvement, the emerging data2vec research, and latest tools & news in tech.
Bitsletter #1: Hashing for ML Splits, Web App Performance, & DALL-E 2 Insights
Discover smarter ways to split ML data, the rise of web edge computing, and how diffusion models are redefining image synthesis. Plus, PyTorch v1.11 and more!
3 Simple Ways To Handle Bigger Datasets In Pandas
Before moving to Spark, here is 3 tips to scale Pandas to bigger datasets.
Introduction To TorchData: The Best Way To Load Data In PyTorch
TorchData is a new library for better data loading in PyTorch. In this post I will show you how to use it and why it's better than Dataset and DataLoader.
1 line to cache slow functions and speed up your Python script
Easily squeeze performance out of your scripts, with only slight modifications. Learn how to leverage caching easily in Python.
Perfect Template To Start Python Projects
Python is great but lacks structure. I detail the issues and provide a GitHub template repository to solve the issue.