Amjad Abu-Rmileh (AmjadHisham)

AmjadHisham

Geek Repo

Location:Jerusalem, Israel

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Amjad Abu-Rmileh's repositories

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

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ASPMI

EE4-13 Adaptive Signal Processing and Machine Intelligence (2017-2018) Coursework

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Analysis-Engineering-and-Modelling

A Repo of various End-to-End analysis in statistical approach, exploratory data analysis (EDA) , feature engineering and modelling.

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applied-machine-learning

A step-by-step guide to get started with Applied Machine Learning

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BanditsBook

Code for my book on Multi-Armed Bandit Algorithms

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blog

Contain all the stuff in my blog

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computer-vision

Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual Recognition

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DataLearn-ML-Intro-2019

The repository of the hands-on introduction to machine learning workshop of the DataLearn 2019 track at DataHack 2019.

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Deep-Neural-Networks-HealthCare

Tangible and Practical Deep Learning Projects Repository for Healthcare such as Cancer, Drug Discovery, Genomic and More

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deeplift

Public facing deeplift repo

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DL-NanoDegreeProjects

This repository contains the 5 projects required to finish the Udacity NanoDegree in DeepLearning

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error-detection

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

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fastai

The fast.ai deep learning library, lessons, and tutorials

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GitHub_Test

This is my github test sample

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Kalman

Some Python Implementations of the Kalman Filter

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keras-text-processing

Sample Keras code for text processing

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livelossplot

Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

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ml-tool-wear

Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as described in article "Self-Supervised Learning for Tool Wear Monitoring with a Disentangled-Variational-Autoencoder"

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neural-networks

Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

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NLP_by_Example

Code for "NLP by Example" book

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qtrader

Reinforcement Learning for Portfolio Management

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RK-Fun

Fun Stuff

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Stock-Price-Predictor

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

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stockPredictor

Predict stock movement with Machine Learning and Deep Learning algorithms

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StockPricePrediction

Stock Price Prediction using Machine Learning Techniques

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Test-stock-prediction-algorithms

Use deep learning, genetic programming and other methods to predict stock and market movements

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