Name: Liran Ben-Zion
Type: User
Company: @datascienceisrael
Bio: Data scientist researcher and Natural Language Processing algorithm developer, with hands on experience in developing NLP systems applications.
Location: Tel Aviv, Israel
Blog: https://www.linkedin.com/in/liran-ben-zion-695a16102/
Liran Ben-Zion's Projects
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(2020) paper
A curated list of awesome computer vision resources
:metal: awesome-semantic-segmentation
Contains resources for the AWS AI/ML workshop at
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Natural language processing (NLP) is a crucial part of artificial intelligence (AI), modeling how people share information. In recent years, deep learning approaches have obtained very high performance on many NLP tasks. In this course, students gain a thorough introduction to cutting-edge neural networks for NLP.
Stanford Deep Learning Course - CS231n
Datahack Haifa - 8.7.2019
Notebooks for my session on Word2Vec for DataHack's DataNights program.
ספר מלא בעברית בנושאים של למידת מכונה ולמידה עמוקה
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
A hands-on workshop on deep neural networks
This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai
Directions overlay for working with pandas in an analysis environment
Useful general functions for data science projects
The fastai deep learning library, plus lessons and tutorials
Easy preprocessing and feature engineering using Featuretools and Sklearn-Pandas
A collection of links and notes on forced alignment tools
Project for forecast company
Create UIs for your machine learning model in Python in 3 minutes
Based on this dataset: https://www.kaggle.com/harlfoxem/housesalesprediction
Deep learning using PyTorch.
HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!
Neural network visualization toolkit for keras
Linear-Regression-on-Boston-Housing-Dataset
Config files for my GitHub profile.