Gil Zeevi's repositories
Segmentation
Image segmentation various methods
gilzeevi25
Config files for my GitHub profile.
Session_based_recommendations
In this repo we tackle the subject of Session based recommendations which relies on implicit feedbacks.
Black-box-Watermarking-tfidf
This repo consists my implementation to https://arxiv.org/abs/2103.05590 paper
Exploring_EMBER_dataset
In this repo we explore the EMBER 2018 dataset - malware/benign classification. we present some Dim-Reduction algo's, feature selections and comparisons between most common and robust classification models: XGBoost, LightGBM, MalConv
Chicago-crimes
Applying some data analysis and machine learning algorithm on chicago crimes dataset
MLops_G2JN
Generalized Automatic Pipeline for inspecting and fixing uncertainties in your data
ScratchDetection
This repo contains well-designed tabular features created through image processing techniques in order to predict a scratch on wafers.
Computer-Vision
outcomes of computer vision IDC 2020 course
covid_papers_inspection
Analyzing and clustering covid papers (full-text / abstract) using compression / transformers methods
Data-generation-using-Optimization
In the following notebook i will suggest a method to generate random data with subjected constraints, using linear/nonlinear Optimization method
Deep_Learning_3600
Deep Learning homework solutions given throughout a course in IDC (Reichman Uni)
Experimenting-With-Levenshtein-Distance.
Some example to present a wonderful and simple method to match strings
Machine-Learning-From-Data
Machine learning algorithms implemented as part of IDC 2021 machine learning from data course
Recommendation_Systems_IDC
Recommendation systems homework solutions given throughout a course in IDC (Reichman Uni)
SQL
Some SQL queries and ERD diagram and schemas that were handled as part of introduction to sql in IDC 2021 course
Statistics_Data_analysis
Statistics & Data analysis which were made during the statistics & Data analysis course in IDC 2021
Trump_Tweets
Trump Tweets analysis and prediction whether it's tweeted via android or iphone.
Uber-rides-in-New-York-City
Applying ML models on 20M records data using Spark MLlib. Ran on EC2 and EMR with several workers