Computer Vision – Deep Learning

C++ number recognition program using ANN

Computer vision has recently experienced a boom in the AI field. It has many applications and it could be very useful to provide a machine the sense. It is used in words and number recognition, to classify objects in clusters and it also gives us the possibility to make autonomous cars. We have seen posts about autonomous cars and computer vision is the next step to achieve this.

We have used a simple backpropagation neural network to recognize the numbers that implement mini-batch learning, momentum, Xavier initialization, and normalization. It is really an advanced ANN that classifies numbers in 10 cluster that represents each one a number between 0 and 9.

Autonomous Driving Car Simulator

Evolutionary algorithm learning process of cars in UE4 C++

Artificial Intelligence

AI is a new field that appeared a few decades ago and has seen an unprecedented growth. The AI approach has been used in numerous fields, such as finance, medicine, music, customer service, and transportation. Some of the big challenges we have to cope with are the computing power and lack of documentation. Big companies such as Google and Apple do not share advances in this field, the secretism characterizes this scientific field and thus the information we can get is very restrictive. 

In this work, we introduce a model of an autonomous car and then examine different algorithms capable of driving the car in a simulated. We also discuss the difficulties we need to deal with such as local minimums, losing diversity, fitness functions, localization, performance, and future applications.

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Genetic Algorithm

Genetic algorithm implementation in neural network

Genetic algorithms (GAs) are a heuristic search and optimisation technique inspired by natural evolution. They have been successfully applied to a wide range of real-world problems of significant complexity.

It is an algorithm that was inspired by the theory of evolution by Charles Darwin. It simulates the process of natural selection where the fittest individuals have higher probabilities to transfer their genes to the next generation. It is usually divided into 5 parts:

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Neural Network Tutorial

C++ Neural Network Backpropagation tutorial from scratch.

In this playlist, I teach the neural network architecture and the learning processes to make the ANN able to learn from a dataset.

The Tutorials are divided in each part of the neural network and we start coding it in C++ in Visual Studio 2017. Once you have completed the tutorial you will be able to design your own neural network and optimize it.

  1. Introduction
  2. Neuron & Layer
  3. Input & Output Layer
  4. Hidden Layer
  5. Neural network
  6. Training
  7. FeedForward & Backpropagation

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Stock Market Data

Web-Scraping Stock Market data using C++ API

This is a complex C++ program that is used as an interface to the client, we only need to execute the main thread and it will automatically update stock market data and store it using the JSON format.

We have used IEX API which is free and has more than 10 indices. It obtains information in real time and it is updated whenever you execute it.


Link

The code it for free on a GitHub repository: StockMarketData Repository

Stock market data & deep learning