Every word from the Federal Reserve moves markets, but their statements are often cryptic. In this talk, I’ll aim to break down my work for a class I took in college on using machine learning and natural language processing (NLP) to analyze Federal Open Market Committee (FOMC) statements and minutes to “predict” interest rate changes. By applying sentiment analysis, text processing, and neural network modeling, I tried to explore whether AI can help us potentially decode central bank language and anticipate monetary policy shifts. I will share some key findings and challenges.
In this talk, I’ll take you on a journey through the creation of xsNumPy, a minimalist implementation of core NumPy features using Python’s standard library. I’ll begin by sharing the inspiration behind the project — my curiosity to unravel the mechanics of NumPy and deepen my understanding of numerical computing. Then, we’ll explore the step-by-step development process, including designing a basic array object, implementing element-wise operations, and tackling challenges like scalability and performance optimization without external libraries. Along the way, I’ll highlight the Pythonic principles and best practices that guided the project, compare xsNumPy’s functionality with NumPy, and reflect on the lessons learned. Finally, I’ll discuss how xsNumPy can serve as a learning tool for developers and educators, and invite the community to join this open-source experiment in computational discovery.
Development (and execution) environments for Ansible can be tricky. I’ll go over how utilizing the devcontainer spec can make it easy to develop Ansible plugins, run Ansible, and share environments with a team so that everyone has the same experience. This concept also extends to python environments in general and can help with complex setups that might include databases, web front ends, and so on.
I have a lamp—I love my lamp. I’ve placed it in the perfect spot, but the on/off switch is so remote that I have to crawl over my couch just to reach it. Wouldn't it be nice if I could simply gesture to my lamp and turn it on? That's exactly what I set out to do. Before long, I was elbow-deep in experiments with MediaPipe for hand tracking, Python for prototyping, NumPy for data crunching, and GPIO for bridging the digital and physical worlds. Little by little, that wild idea took shape, transforming into a live system that lets you wave goodbye to remotes forever.
Join me at ChiPy, where I’ll share how this gesture-recognition project grew from a late-night epiphany into a fully functional smart home solution. We’ll explore how combining computer vision and IoT opens up new ways to interact with our environment—no more clunky remotes or app-hopping. Get ready for a glimpse into the future of home automation, driven by intuitive gestures and powered by Python.
Quick script to pull data from an API and perform some basic cleaning/transformation/filtering using Pandas.
TypeScript adds the structure and safety of static types to JavaScript without sacrificing its flexibility. In this lightning talk, I’ll explore why it’s a key player in modern development and why it’s become a go-to choice for building scalable, reliable web applications.
HTML is the best language after python because all these reasons
I will be talking about Swift and the general experience of mine using it and also pythonkit an framework that encapsulates Python
A quick overview of golang and how it compares to python.