Fares Sayah (fares-ds)

fares-ds

Geek Repo

Company:LogicAI

Location:Sétif, Algeria

Home Page:linkedin.com/in/fares-sayah/

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Fares Sayah's repositories

Predicting-the-closing-stock-price-of-APPLE-using-LSTM

In this project we will be looking at data from the stock market, particularly some technology stocks. We will learn how to use pandas to get stock information, visualize different aspects of it, and finally we will look at a few ways of analyzing the risk of a stock, based on its previous performance history.

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Data-Science-Projects-From-Kaggle

Data science projects from the Kaggle website: Data Analysis, Data Visualization, Machine Learning, Time Series Analysis, Computer Vision, Natural Language Processing, Predictive Modeling ...

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beginner_python_projects

This repository contain 10 python friendly projects for bigenner to start learning python by building projects.

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Machine-Learning-Algorithms-Tutorials

Basic Machine Learning Algorithms tutorials (Linear Regression, Logistic Regression, SVM, Random Forest, Bagging, KNN, K-Means ...)

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Minimizing-Churn-Rate-Through-Analysis-of-Financial-Habits

The objective of this model is to predict which users are likely to churn, so that the company can focus on re-engaging these users with the product. These efforts can be email reminders about the benefits of the product, especially focusing on features that are new or that the user has shown to value.

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Natural-Language-Processing

Natural Language Processing projects and Tutorials

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Predicting_Loan_Defaulters_Using_Deep_Learning

In this case study, we will also develop a basic understanding of risk analytics in banking and financial services and understand how data is used to minimise the risk of losing money while lending to customers.

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Cifar-10_Image_Classification_Using_CNNs

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

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Credit-Card-Fraud-Detection

The Credit Card Fraud Detection Problem includes modeling past credit card transactions with the knowledge of the ones that turned out to be a fraud. This model is then used to identify whether a new transaction is fraudulent or not. Our aim here is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications.

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Machine_Learning_Deployment_with_Streamlit

In this project, I used data from a Kaggle competition and build machine learning models to classify a text as Disaster or Not. The model is deployed on Heroku.

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Natural-Language-Processing-with-Python

Can you use this dataset to build a prediction model that will accurately classify which texts are spam?

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Real-or-Not-NLP-with-Disaster-Tweets

Predict which Tweets are about real disasters and which ones are not

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SIIM-ISIC-Melanoma-Classification

Identify melanoma in lesion images Kaggle Competition

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Time_Series_Analysis_Tutorial

A time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time.

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pandas

Full data analysis and data visualization projects notebooks using Pandas, Numpy, matplotlib and seaborn

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phonondos_e3nn

Code Repository for "Direct prediction of phonon density of states with Euclidean neural network"

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talk-to-youtube-videos

Youtube assitant using OpenAI, Langchain, and FastAPI - Using this API you can ask questions directly to your favorate podcast.

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workshop

The Materials Project Workshop Curriculum

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hlb-CIFAR10

Train to 94% on CIFAR-10 in less than 10 seconds on a single A100, the current world record. Or ~95.77% in ~188 seconds.

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ocr-api-application

A simple FastAPI application to extract text from images

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