Doaa Ahmed's starred repositories

LSTM-For-Stock-Market-Prediction

LSTM For Stock Market Prediction

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Stanford-Project-Predicting-stock-prices-using-a-LSTM-Network

Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).

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pandas_exercises

Practice your pandas skills!

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Geospatial_Data_with_Python

Introduction to Geospatial Data with Python

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chefboost

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

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Apply-Probability-Distributions-in-dataset

in this Jupyter notebook we explain probability distributions and apply them in real datasets

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Data-Science-Interview-Questions-Answers

Curated list of data science interview questions and answers

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tutorials

This repository contains Machine Learning tutorials using Jupyter notebooks.

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Neural-Net-with-Financial-Time-Series-Data

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow

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Tensorflow-Bootcamp

TensorFlow bootcamp course by Udemy

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