Notas en español, recursos, ejemplos de Artificial Neural Networks (Redes Neuronales Artificiales) y Deep Learning (Aprendizaje Profundo).
Estos recursos están escritos en español, pero muchas veces contienen expresiones en inglés (como Deep Learning). Hay términos en inglés que son tan usados que preferí dejarlos en el idioma original, pero siempre dando una traducción libre. Muchas veces, los ejemplos de código contienen nombres en inglés, pero espero también que en la explicación quede claro cuál es la traducción.
Pongo varias referencias en inglés, porque es el contenido más difundido. Igual espero poder explicar algunos de los temas en estos recursos en español.
Los temas a tratar, en este repositorio y otros, son:
- Historia de Redes Neuronales
- Perceptrones
- Redes Neuronales Feedforward
- Algoritmo de Backtracking
- Redes Convolucionales
- Redes Recurrentes
- Redes Residuales
- Aplicaciones
TBD
A completar
- Perceptron
- Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
- Neural networks from scratch for Javascript linguists (Part1 — The Perceptron)
- Fast.AI
- Onnx: Open Neural Network Exchange Format
- Implementing The Perceptron Algorithm From Scratch In Python
- The evolution of neural networks
- A Gentle Introduction to LSTM Autoencoders
- How Do Neural Networks Learn?
- Self-organizing map
- Building a Feedforward Neural Network from Scratch in Python
- To The Point: A Quick Neural Network in JavaScript
- Understanding Activation Functions in Neural Networks
- Rectifier (neural networks)
- Softmax function
- Why do we use ReLU in neural networks and how do we use it?
- A Practical Guide to ReLU
- Rectified-Linear unit Layer
- ReLU and Softmax Activation Functions
- Rectified Linear Units (ReLU) in Deep Learning
- My attempt to understand the backpropagation algorithm for training neural networks
- Backpropagation
- Which is best for training an artificial neural network, a backpropagation algorithm, or a genetic algorithm?
- Gradient Descent and Backpropagation
- What is the difference between SGD and back propagation?
- Deep Learning Basics: Neural Networks, Backpropagation and Stochastic Gradient Descent
- Build a flexible Neural Network with Backpropagation in Python
- The Backpropagation Algorithm Demystified
- Convolutional Neural Networks (CNNs / ConvNets)
- A Beginner's Guide To Understanding Convolutional Neural Networks
- A Beginner's Guide To Understanding Convolutional Neural Networks Part 2
- Introducing convolutional networks
- Convolutional neural networks in practice
- Convolution
- Visualizing and Understanding Convolutional Networks
- What is meant by feature maps in convolutional neural networks?
- Convolution
- Pool Layer
- GoogleNet
- Convolutional Neural Networks (CNNs / ConvNets)
- ImageNet Classification with Deep Convolutional Neural Networks
- Convolution neural nets, Part 2
- 3D Visualization of a Convolutional Neural Network
- A Guide for Building Convolutional Neural Networks
- Very Deep Convolutional Networks for Large-Scale Visual Recognition
- Paper: Very Deep Convolutional Networks for Large-Scale Image Recognition
- Convolutional Neural Networks — Simplified
- How To Teach A Computer To See With Convolutional Neural Networks
- Implementation of Training Convolutional Neural Networks
- Image Tagger - A Convolutional Neural Network Based Image Classifier
- Everything you need to know to master Convolutional Neural Networks
- Deep Learning with Convolutional Neural Networks
- Visualising Filters and Feature Maps for Deep Learning
- An Idea From Physics Helps AI See in Higher Dimensions
- Recurrent neural networks
- Long short-term memory
- Generating News Headlines with Recurrent Neural Networks
- Understanding LSTM Networks
- Attention and Augmented Recurrent Neural Networks
- The Unreasonable Effectiveness of Recurrent Neural Networks
- Neural Networks and Deep Learning (online book)
- Deep Learning
- Understanding deep learning requires rethinking generalization
- Deep Learning
- Deep Learning Book
- Dive into Deep Learning
- Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data
- Learning Deep Learning — Step 1
- Deep Learning: Feedforward Neural Networks Explained
- Deep Learning Structure Guide for Beginners
- Deep Learning Cheat Sheats
- The Next Frontier in AI: Nothing
- La Siguiente Gran Revolución: NLP
- Language Models are Few-Shot Learners
- GPT-3: Language Models are Few-Shot Learners
- A state-of-the-art open source chatbot
- Unsupervised Translation of Programming Languages
- Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention)
- The Illustrated Transformer
- A Deep Dive into Reinforcement Learning
- Deep Q-Learning
- Schooling Flappy Bird: A Reinforcement Learning Tutorial
- What’s New in Deep Learning Research: How Google Uses Reinforcement Learning to Ask All the Right Questions
- Combination of Deep and Reinforcement Learning
- Playground
- Play with neural networks
- Synaptic
- Accord.NET Framework
- Deep Learning Libraries
- PyTorch Neural Networks
- ConvNetJS, Deep Learning in Your Browser
- StarSpace
- StarSpace: Learning embeddings for classification, retrieval and ranking
- TensorRT
- Google Trax
- CAN: Creative Adversarial Networks Generating “Art” by Learning About Styles and Deviating from Style Norms
- Generative Adversarial Networks for Text Generation — Part 2: Reinforcement Learning'
- 5 New Generative Adversarial Network (GAN) Architectures For Image Synthesis
- The Rise of Generative Adversarial Networks
- You can build a neural network in JavaScript even if you don’t really understand neural networks)
- Nearest Neighbors with Keras and CoreML
- Neural Network Embeddings Explained
- Python Machine Learning Prediction with a Flask REST API
- Deep Learning, NLP, and Representations
- Deep Lip Reading: a comparison of models and an online application
- Sequence to Sequence Learning with Neural Networks
- Loc2Vec: Learning location embeddings with triplet-loss networks
- A 2019 Guide to Speech Synthesis with Deep Learning
- Neural Networks, Simon Haykin
- Fundamentals of Deep Learning, Nikhil Buduma (2017, O’Reilly)
- Anthony L. Caterini, Dong Eui Chang - Deep Neural Networks in a Mathematical Framework (2018, Springer)
- Charu C. Aggarwal - Neural Networks and Deep Learning. A Textbook (2018, Springer)
- Ian Goodfellow, Yoshua Bengio, Aaron Courville - Deep Learning (2016, The MIT Press)
- Deep Reinforcement Learning Hands-On, Maxim Lapan, Packt
- Deep Learning with Python, A Hands-On Introduction, Nikhil Ketkar, Apress (2017)
- AlphaGo Zero: Learning from scratch
- Google's New AlphaGo Breakthrough Could Take Algorithms Where No Humans Have Gone
- This More Powerful Version of AlphaGo Learns on its Own
- AlphaGoZero
- Mastering the game of Go with deep neural networks and tree search
- Mastering the game of Go without human knowledge
- Understanding AlphaGo
- The 3 Tricks That Made AlphaGo Zero Work
- Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
- Beyond Monte Carlo Tree Search: Playing Go with Deep Alternative Neural Network and Long-Term Evaluation
- 'AlphaGo' es el documental de Netflix que mejor explica lo que supuso la victoria de la IA de Google al campeón de Go
- La máquina supera al humano: el mejor jugador de Go pierde frente a la inteligencia artificial de Google
- AlphaGo gana la última partida a Lee Sedol y cierra con un contundente 4-1 final
- AlphaGo vs Lee Sedol Match 1 Game Replay (Google DeepMind Challenge Match)
- Match 1 15 min Summary - Google DeepMind Challenge Match
- An open-source implementation of the AlphaGoZero algorithm
- Mastering the game of Go without human knowledge
- How the artificial-intelligence program AlphaZero mastered its games
- Innovations of AlphaGo
- Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper
- Las diferencias entre AlphaGo Fan, AlphaGo Lee, AlphaGo Master y AlphaGo Zero
- AlphaGo versus Lee Sedol
- A former world champion of the game Go says he's retiring because AI is so strong: 'Even if I become the No. 1, there is an entity that cannot be defeated'
- AlphaGo vs. AlphaGo; Game 36: The ladder game
- AlphaGo Zero vs. AlphaGo Lee with Michael Redmond 9p: Game 1
- Google's self-learning AI AlphaZero masters chess in 4 hours
- In Two Moves, AlphaGo and Lee Sedol Redefined the Future
- AlphaZero demonstrates synergy to Stockfish
- Is AlphaGo Really Such a Big Deal?
- AI Ruined Chess. Now, It’s Making the Game Beautiful Again
- Viola–Jones object detection framework
- Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
- Spatial pyramid pooling (SPP)
- How does the spatial pyramid matching method work?
- YOLO — You only look once, real time object detection explained
- Real-time Object Detection with YOLO, YOLOv2 and now YOLOv3
- YOLO: Real-Time Object Detection
- You Only Look Once (YOLO): Unified, Real-Time Object Detection
- YOLO9000: Better, Faster, Stronger
- Image Detection with YOLO-v2 (pt.8) Custom Object Detection (Train our Model!)
- YOLO Object Detection (TensorFlow tutorial)
- YOLO Object Detection (TensorFlow tutorial)
- Histogram of Oriented Gradients
- Training a better Haar and LBP cascade based Eye Detector using OpenCV
- Histogram of oriented gradients
- Histograms of oriented gradients for human detection
- Darknet Convolutional Neural Networks
- SSD: Single Shot MultiBox Detector
- Single Shot detectors
- SSD object detection: Single Shot MultiBox Detector for real-time processing
- Fast Region-based Convolutional Neural Network
- R-CNN, Fast R-CNN, Faster R-CNN, YOLO — Object Detection Algorithms
- Review: Fast R-CNN (Object Detection)
- Introduction to How Faster R-CNN, Fast R-CNN and R-CNN Works
- Udacity Vehicle Detection faster rcnn
- Mask R-CNN
- Human Instances Segmentation (Faster RCNN + UNet) in Supervisely
- Image augmentation for machine learning experiments
- Image augmentation for machine learning experiments: documentation
- Siamese Neural Networks for One-shot Image Recognition
- An open source library for face detection in images. The face detection speed can reach 1500FPS.
- How does the Inception module work in GoogLeNet deep architecture?
- Regularized Evolution for Image Classifier Architecture Search
- Review: R-CNN (Object Detection)
- How The Deep Learning Approach For Object Detection Evolved Over The Years
- A Deep Learning Approach for Tumor Tissue Image Classification
- Using Machine Learning for Classification of Cancer Cells
- A Deep Learning Approach for Cancer Detection and Relevant Gene Identification
- An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images
- Google’s Machine Learning Model can Detect Cancer in Real-Time
- Deep Learning Based Automatic Immune Cell Detection for Immunohistochemistry Images
- Deep Learning for Cancer Diagnosis: A Bright Future
- OpenFace
- FaceNet: A Unified Embedding for Face Recognition and Clustering
- Facial recognition system
- Facial recognition api for Python and the command line
- One Shot Learning with Siamese Networks in PyTorch
- Siamese Network & Triplet Loss
- Implementation of triplet loss in TensorFlow
- Triplet loss and its uses
- Apple's New iPads Embrace Facial Recognition
- How Facial Recognition Systems Work
- HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
- Learning Invariant Deep Representation for NIR-VIS Face Recognition
- Luxand FaceSDK
- Face Recognition
- The Guardian: Face Recognition
- 20 Facial Recognition Search Engines For Online Photo Search
- 8 Best Facial Recognition Search Engines to Search Faces Online
- Machine Learning is Fun! Part 4: Modern Face Recognition with Deep Learning
- How to set up face verification the easy way using HTML5 + JavaScript
- Face recognition with OpenCV: Haar Cascade
- An Intro to Deep Learning for Face Recognition
- Making your own Face Recognition System
- Building a Facial Recognition Pipeline with Deep Learning in Tensorflow
- Face Recognition for Beginners