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angular-cero-experto

angular-challenges

Set of Angular challenges to practise and train on Angular

audiocraft

Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable music generation LM with textual and melodic conditioning.

backpropygation

Step-by-step guide to compute gradients, update weights, and fine-tune the model for improved performance.

car-dealership-nest-js

django-celery-redis

fastapi-auth

frontend-angular-canvas

gradient-descent-algorithm-in-1-dimension

This repository contains an implementation of the gradient descent algorithm in one dimension. Gradient descent is a popular optimization algorithm used to find the minimum of a function. It iteratively adjusts the parameters of the function in the direction of steepest descent, guided by the gradient of the function.

gradient-descent-algorithm-in-2-dimensions

The Gradient Descent algorithm is an iterative optimization algorithm used to find the minimum of a function. In this implementation, we focus on finding the local minimum of a function in a 2-dimensional space.

job-swe-backend

This GitHub repository houses a powerful Python backend built using Django and Django Rest Framework. It enables the creation and management of job listings, allowing users to post jobs and apply seamlessly. Empower your job platform with this reliable and scalable solution.

mini-neural-network

Welcome to the "mini neural network" repository! This project is a comprehensive guide and implementation of neural network training from the ground up, aimed at providing a deep understanding of the inner workings of neural networks using Python.

neural-networks-raw-cpp

This repository is dedicated to building neural networks from scratch in raw C++, which means we will implement all the necessary components, including data preprocessing, weight initialization, feedforward propagation, backpropagation, and gradient descent. By working with the fundamental building blocks of neural networks.

neural-networks-raw-python

This repository is dedicated to building neural networks from scratch in raw Python, which means we will implement all the necessary components, including data preprocessing, weight initialization, feedforward propagation, backpropagation, and gradient descent. By working with the fundamental building blocks of neural networks.