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airline_passenger_referral_prediction

The given data includes airline reviews from 2016 to 2019 for popular airlines around the world with multiple choice and free text questions. Data is scrapped in spring2019.The main objective is to predict whether passengers will refer the airline to their friends.

boston_house_price_prediction

Boston House Price Prediction project involves several stages of data preprocessing, feature engineering, model building, and deployment. I have used pkl file for serialize the object and convert it into a “byte stream and also used a Flask for make front-end . The project's output can be useful in real estate businesses, homeowners, and prospect.

data-science-interview-resources

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

dataset

dsa-with-python

eda-global-terrorism-dataset

EDA on Global Terrorism Dataset project is to explore and analyze the data to understand the patterns and trends of terrorism, such as the locations, frequency, types of attacks, and perpetrators involved.

end_to_end_animal_classification_using_mlflow_dvc

enhancing-manufacturing-efficiency-through-data-driven-insight-powerbi

font_recognition_using_ml

The Font Recognition project employs a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory Recurrent Neural Networks (LSTM RNNs) to recognize fonts from images. This hybrid architecture is chosen for its ability to capture both spatial features from images (via CNNs) and temporal dependencies within sequences of features

hacktoberfest-2022

Contribute in this repository by raising genuine PR. Get verified, merged and earn the free swags from Hacktoberfest 2022.

interview-question-data-science-

ner-with-bert

The goal of this project is to develop a Named Entity Recognition (NER) system that can identify and classify named entities (such as names of people, organizations, locations, dates, etc.) in a given text using the BERT model from Hugging Face's Transformers library.

online_retail_customer_segmentation

The main objective of this project is to group customers with similar behavior and characteristics into segments to better understand their needs and preferences. The unsupervised machine learning techniques used in this project include K-means clustering ,hierarchical clustering and DBScan Clustering.

patient-s-condition-classification-using-drug-reviews

The primary objective of this project is to develop a robust system capable of accurately classifying patient conditions solely based on their reviews. By leveraging advanced NLP techniques, the project aims to streamline the categorization process and provide valuable insights into patient health status.

python-practise-problems

stock_market_prediction_and_forecasting_using_bidirectional_lstm_rnn

Utilizing advanced Bidirectional LSTM RNN technology, our project focuses on accurately predicting stock market trends. By analyzing historical data, our system learns intricate patterns to provide insightful forecasts. Investors gain a robust tool for informed decision-making in dynamic market conditions. With a streamlined interface, our solution

talk_with_pdf

Talk_with_PDF is a powerful, AI-driven solution designed to automate the extraction of information and generation of answers based on PDF documents. By integrating OpenAI's advanced language models and embeddings, this system provides accurate and contextually relevant responses, making it an invaluable tool for education, business, and research.

the-grand-complete-data-science-materials

unlocking-financial-insights-in-banking-data-tableau

unveiling-covid-19-dynamics-in-india-through-excel-dashboard-analytics

weather-app

yes_bank_stock_closing_price

Yes-Bank-Stock-Closing-Price-Prediction refers to a type of project or task in the field of data science and machine learning that involves developing predictive models to estimate the Closing Price of stock