keitazoumana

keitazoumana

Title, Link, Video
5 Python open-source tools to extract text and tabular data from PDF Files, https://towardsdatascience.com/5-python-open-source-tools-to-extract-text-and-tabular-data-from-pdf-files-9359cdde6b56, 
When Should You Consider Using Datatable Instead of Pandas to Process Large Data?, https://towardsdatascience.com/when-should-you-consider-using-datatable-instead-of-pandas-to-process-large-data-29a4245f67c6, 
Convert Any Type of Document to Text With Apache Tika Using Python API, https://medium.com/mlearning-ai/convert-any-type-of-document-to-text-with-apache-tika-using-python-api-ff306c467b3, 
Collect Data From Reddit and Twitter— 600+ Million Monthly Active Users Platforms, https://medium.com/mlearning-ai/web-scraping-f854c9c30778, 
Knockknock — Probably The Best Python Library For Notifications, https://towardsdatascience.com/knockknock-probably-the-best-python-library-for-notifications-136bdf788f8a, 
Extract Text Written in Different Languages from Images with Python, https://towardsdatascien

keitazoumana

keitazoumana

Title, Link, Video
Do You Want To Cluster Unlabeled Text Data? Try Out Topic Modeling, https://towardsdatascience.com/do-you-want-to-cluster-unlabeled-text-data-try-out-topic-modeling-235795ae7cb7,
Financial Text Classification With Deep Learning Using FinBERT, https://medium.com/mlearning-ai/financial-text-classification-with-deep-learning-using-finbert-51a73b393a08, 
Named Entity Recognition with Spacy and the Mighty roBERTa, https://towardsdatascience.com/named-entity-recognition-with-spacy-and-the-mighty-roberta-97d879f981, https://youtu.be/OLwYBSE64m4
Scientific Documents Similarity Search With Deep Learning Using Transformers (SciBERT), https://towardsdatascience.com/scientific-documents-similarity-search-with-deep-learning-using-transformers-scibert-d47c4e501590, 
Meet BERTopic— BERT’s Cousin For Advanced Topic Modeling, https://towardsdatascience.com/meet-bertopic-berts-cousin-for-advanced-topic-modeling-ea5bf0b7faa3, https://youtu.be/sZcGuYHWN_w
Unsupervised Multilingual Text Classification With Zero

keitazoumana

Title, Link, Video
Create An Awesome Streamlit App & Deploy it With Docker, https://towardsdatascience.com/create-an-awesome-streamlit-app-deploy-it-with-docker-a3d202a636e8, 
Machine Learning models monitoring made easy with Mlfow - a concrete use case with Python API, https://medium.com/mlearning-ai/machine-learning-models-monitoring-made-easy-with-mlfow-a-concrete-use-case-with-python-api-334691936a7a, 
When Your Machine Learning model teams up with Django REST API - A successful deployment into production, https://towardsdatascience.com/when-your-machine-learning-model-teams-up-with-django-rest-api-a-successful-deployment-into-2f720bd67ff1, 
NLP MLops Project With DagsHub — Multi-Language Sentiment Classification Using Transformers — Part 1, https://towardsdatascience.com/nlp-mlops-project-with-dagshub-multi-language-sentiment-classification-using-transformers-fcbe6164b171, 
NLP MLops Project With DagsHub — Deploy Your Streamlit App On AWS EC2 Instance — Part 2, https://towardsdatascience.com/nlp-mlops-pr

keitazoumana

Title, Link, Video
Transfer Learning: Understand the Big Picture & Make the Right Choices for Your Use Case, https://medium.com/geekculture/transfert-learning-understand-the-big-picture-make-the-right-choices-for-your-use-case-bb4abc3972e6, 
Overview Of 4 Model Validation Approaches to Mitigate Overfitting Problem, https://towardsdatascience.com/overview-of-4-model-validation-approaches-to-mitigate-overfitting-problem-6d2eecdf8053, 
eXplainable AI (XAI): LIME & SHAP Two Great Candidates to Help You Explain Your Machine Learning Models, https://towardsdatascience.com/explainable-ai-xai-lime-shap-two-great-candidates-to-help-you-explain-your-machine-learning-a95536a46c4e, 
Using Gradio To Create Apps For Your Machine Learning Models, https://medium.com/geekculture/using-gradio-to-create-apps-for-your-machine-learning-models-569247f217ef, https://www.youtube.com/watch?v=OgQyZ4LApnY
How to Perform KMeans Clustering Using Python, https://towardsdatascience.com/how-to-perform-kmeans-clustering-using-python-7cc296ce

keitazoumana

Title, Article Link, Video
A simple way to understand Association Rule from the Customer Basket Analysis Use Case, https://towardsdatascience.com/a-simple-way-to-understand-association-rule-from-the-customer-basket-analysis-use-case-c7bcd75bdec1, None
Different Metrics to Evaluate Binary Classification Models and Some Strategies to Choose the Right One, https://towardsdatascience.com/different-metrics-to-evaluate-binary-classification-models-and-some-strategies-to-choose-the-right-911ef72a107b,  None
Introduction to Mito: Spreadsheet for Data Scientists That Also Generates Python Codes, https://towardsdatascience.com/introduction-to-mito-spreadsheet-for-data-scientists-that-also-generates-python-codes-642b4c2d7dfc,  None
When R Meets SQL to Query Dataframes, https://towardsdatascience.com/when-r-meets-sql-to-query-data-frames-a94d9d92b0f2, 
5 Essential Tools to Start a Career in Data Science and Data Analytics, https://towardsdatascience.com/5-essential-tools-to-start-a-career-in-data-science-and-data-analyti

keitazoumana

"""
Individual imports
"""
from sklearn.metrics import precision_score, recall_score, f1_score

y_true = [0, 1, 2, 0, 1, 2]
y_pred = [0, 2, 1, 0, 0, 1]

print("Precision: ", precision_score(y_true, y_pred, average='macro'))
print("Recall: ", recall_score(y_true, y_pred, average='macro'))

keitazoumana

import os
import faiss
import torch
import skimage
import requests
import numpy as np
import pandas as pd
from PIL import Image
from io import BytesIO
import IPython.display

keitazoumana

%%bash 
# Uncomment this if using for the first time. -qqq for ZERO-OUT
pip3 -qqq install transformers torch datasets

# The following two libraries avoid the UnidentifiedImageError
pip3 -qqq install gdcm
pip3 -qqq install pydicom
pip -qqq install faiss-gpu