This repository contains the implementations of different neural network algorithms. The implementation is done without using any library functions.
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Updated
Apr 17, 2021 - Jupyter Notebook
This repository contains the implementations of different neural network algorithms. The implementation is done without using any library functions.
In this repo I am trying to build test automation framework using machine learning in the error detection and prediction. By using ML the framework will be able to recover from the issue will face during execution process.
A machine learning model that can classify real and AI generated images
A neural machine translation framework based on transformer architecture, with most of the code refered to Li Mu's 《Dive into deep learning》, has completely removed its dependence on D2L.
Introducing the data-driven concept through neural networks to price an option whose volatility is measured as a stochastic process.
An Artificially Intelligent Medical Assistant Chat Bot created in 2021 as a project for my introductory course to artificial intelligence in the British University in Dubai
Tensorix is a minimalistic and highly compatible Python library designed to facilitate efficient communication with GPUs.
The perceptron algorithm is the basic algorithm for classification, which serves as the backbone of the Neural Networks and SVM linear classification. This code will provide a deep understanding of the algorithm by taking you through it from scratch.
Deep Learning project to predict the outcomes of football matches
ML Classification model to approve or deny credit card applications.
Exploring deep learning networks and solving diverse problems through fun and practical implementations, from basics to advanced techniques.
Binary classification of 50,000 highly polarized IMDB reviews using keras.
Exploring GloVe Embeddings
Training and saving a model using cats_vs_dogs datasets to perform image classification
My projects and practices on various segments of machine learning and deep learning.
Using a supercar and a common car datasets, we analyzed car variables with prices. Also created two machine learning models to create more relationships between variables and predict prices
Building Simple Neural Network Model from Scratch Using Python to Identify Patterns in Dataset to Make Predictions.
Face ID Authentication Website
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