Galina-Blokh's repositories
flask-heroku-app
NLP WEB app for fake news vs satire classification. Flask, Heroku, Transfer learning
selenium_scraper
A data mining project: data collection with Selenium Python framework
ai_assignment_aidock
data mining NLP project
Auto-Ticket-Assignment
Using NLP to build a text classification model for auto-ticket asisgnment problem
distilbert_bynary_classification
A notebook for a medium article about text classification with Hugging Face DistilBert and Tensorflow 2.0
jep-java-python
example of calling python from java
datasets
🤗 Fast, efficient, open-access datasets and evaluation metrics in PyTorch, TensorFlow, NumPy and Pandas
fake-news-classification
Classify news stories as fake or truthful to help a social media platform reduce its risk of negative PR and related financial losses using Natural Language Processing (NLP) and Machine Learning
gcp-practice
practical tasks and notebooks from GCP ML specialisation
gcp-python-docs-samples-official
Code samples used on cloud.google.com
gcp-training-data-scientist
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
GiveMeCredit_Top5_Solution_Kaggle
Banks play a crucial role in market economies. They decide who can get finance and on what terms and can make or break investment decisions. For markets and society to function, individuals and companies need access to credit. Credit scoring algorithms, which make a guess at the probability of default, are the method banks use to determine whether or not a loan should be granted. This competition requires participants to improve on the state of the art in credit scoring, by predicting the probability that somebody will experience financial distress in the next two years. The goal of this competition is to build a model that borrowers can use to help make the best financial decisions.
itc_bootcamp_winter2020
Practice in data science
ml-basics
Exercise notebooks for Machine Learning modules on Microsoft Learn
my_public_presentation_python2vs3
python2 vs python 3 main differences
spaCy
đź’« Industrial-strength Natural Language Processing (NLP) with Python and Cython
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.