Deep-learning - TechnoScripts

deep-learning

Deep learning tutorials in Python covering neural networks, training, and common frameworks.

DL: Introduction to Neural Networks, Perceptron to Multi-Layer

A Python neural network is simpler than it sounds: it starts with the single perceptron that mimics one brain cell and builds up to multi-layer networks that can approximate almost any function. This post explains what neural networks really are, showing how layers of simple math operations stack together to solve problems no single equation could ever handle. “A neural network is essentially a function approximator. Give it enough neurons and layers, and it can learn any mapping from inputs ... Read More

ML: Polynomial & Regularization (Ridge, Lasso)

You build a model, it nails every point in your training data, then it falls apart the moment fresh numbers show up. That gap between the practice test and the real exam is exactly what ridge lasso regression is built to close. This guide starts with polynomial regression for curved data, then leans on Ridge (L2) and Lasso (L1) to rein in that overfitting, with every example run on scikit-learn. “The art of statistical learning is finding the right level ... Read More

Python: Virtual Environments & Dependency Management

A Python virtual environment, or venv for short, gives every project its own private box of packages, so two projects can need two different versions of the same library and neither one breaks. This post shows you why virtual environments exist, how activation quietly changes your PATH, how to pin dependencies in requirements.txt, and how to stop one project from ever poisoning another again. “The Python development world is filled with smart engineers, but dependency management can humble even the ... Read More