Khosiyat/Titanic_LogisticRegression

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Created over 3 years ago
Updated over 3 years ago

Khosiyat/Titanic_LogisticRegression

Khosiyat

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KMeans-ML-AI

NLP to automate the discovery of how scientific data are referenced in publications

Jupyter Notebook

Stop-Words-with-NLTK

Stop words with NLTK

Tokenize-with-NLTK

Tokenizing Words and Sentences with NLTK package

Stemming-words-with-NLTK

Stemming words with NLTK

MedAssistance_Bot

The model of this bot is trained with a medical data. The app is development stage yet.

Algorithms

Part-of-Speech-Tagging-with-NLTK

Part of Speech Tagging with NLTK

Exploratory-data-analysis-M5-Forecasting---Accuracy

Exploratory data analysis | M5 Forecasting - Accuracy

coffeePreference_Prediction

Food_Store

ML models are applied in this website to analize customer data in order to provide clear guide recommendation system of the website and to analize nutrients such as calorie, healthy nutrients consumer needs, etc. The project is on the development stage yet.

GradientBoostingRegressor

Building algorithms to rate the complexity of reading passages for grade 3-12 classroom use

Jupyter Notebook

Titanic_DecisionTree

numpy_Tutorial

Gulcheera Academy https://www.youtube.com/channel/UCtMWMHigd_teUWl0QecYMhg

regex-Remove-Pattern

regex-Extract-telNumbers

Named-Entity-Recognition-with-NLTK

Named Entity Recognition with NLTK

regex-Extract-Emails

Titanic_RAndomForest

regex-Extract-Weblinks

Exploratory_data_analysis.py

500-S-P-capital-Prediction

LeetCode-DataBase-Pandas-SQL

LeetCode DataBase Pandas SQL

LeetCode-Problems--Data-Structures

Khosiyat-Sobir

Foodie_Platform_sourceCode

A Platform where Foodies can share their food experiences and applied ML models in this platform analize nutrients such as calorie, healthy nutrients consumer needs, etc. The project is on the development stage yet. Source Code can be shared if it is requested(but it can be shared with whom those contribute for this project)

GeekyPinkers

Jupyter Notebook

Foodie_Platform

A Platform where Foodies can share their food experiences and applied ML models in this platform analize nutrients such as calorie, healthy nutrients consumer needs, etc. The project is on the development stage yet.

algorithm_task

selenium_viewsYouTube.py

web-harvesting

extracting data of S&P capital market

Uzbek_Corpus_Project

Predict-Future-Sales-

Wordnet-with-NLTK

Wordnet with NLTK

LEMMATIZE

Regex-Parsing

CHUNKING (Regex Parsing)

Unit-Testing-Pyhton-Django

Unit Testing Pyhton Django

Google-Quest-Challange

Computers are really good at answering questions with single, verifiable answers. But, humans are often still better at answering questions about opinions, recommendations, or personal experiences. Humans are better at addressing subjective questions that require a deeper, multidimensional understanding of context - something computers aren't trained to do well…yet.. Questions can take many forms - some have multi-sentence elaborations, others may be simple curiosity or a fully developed problem. They can have multiple intents, or seek advice and opinions. Some may be helpful and others interesting. Some are simple right or wrong.