A Passionate Technologists' Journal

Pocket TTS Demo: I cloned Rajnikanth's voice on my machine, kinda! I tried pocket-tts from kyutai labs and, with a short audio clip, ended up with a voice that sounded oddly familiar. No GPU setup, no cloud stack, just with my mac. Pocket TTS is a lightweight, CPU-friendly TTS demo. It can speak with a built-in voice or clone a voice from a short audio clip. 🔗 Demo Repository: Check out the full demo on GitHub The repo stays lean: one entry script ( src/pocket_tts_demo.py ), a Docker runner ( run.sh ), and helpers that keep the flow smooth. Both paths lead to the same moment: your text turns into a WAV file under output/ . The quick path If you like containers, the flow is: ./run.sh build ./run.sh run --voice alba --text "Hello, this is a test" --output /app/output/test.wav If you prefer Python: pip install pocket-tts --no-deps pip install ...

My Journey Building a Production-Ready ML Pipeline: House Rent Prediction How I learned to build a scalable machine learning system from scratch using Apache Spark, Kubernetes, and AWS services 🎯 The Learning Challenge When I started my ML learning journey, I wanted to build something real - not just another tutorial project. I decided to create a house rent prediction system that could actually be used in production. The challenge was daunting: I needed to build a system that could: Process thousands of house listings efficiently Train ML models with complex feature engineering Serve predictions in real-time Scale automatically based on demand Maintain data lineage and reproducibility ...