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3_streamlit_qa_app

5_streamlit_custom_chatgpt

analyzing_cia_factbook_data_using_sql

In this project, we'll work with data from the CIA World Factbook, a compendium of statistics about all of the countries on Earth.

analyzing_nyc_high_school_data

This project will be comparing demographic factors such as race, income, and gender with SAT scores to determine whether the SAT is a fair test.

answering_business_questions_using_sql

Using the Chinook database and SQL this project will be focused on answering business related questions.

attractive_apps

Data analysis of apps in the Google's play store and Apple's app store to identify the criteria for attractive apps

building_a_spam_filter_with_naive_bayes

For this project, our goal is to create a spam filter that classifies new messages with an accuracy greater than 80% .

customer_segementation_with_sentence_embeddings

direct_marketing_analysis

Analysis to identify the variables closely linked to customers purchasing additional services and examine how these variables affect the chances of a successful marketing strategy.

ebay_car_sales_data

In this project will involve working with a dataset of used cars from eBay Kleinanzeigen. The aim of this project is to clean the data and analyze the included used car listings.

employee-exit-surveys

In the guided project, we'll work with exit surveys from employees.

finding_the_best_markets_to_advertise_in

The goal in this project is to find out the two best markets to advertise their product in.

gender_gaps_degrees

In this project will data, we will explore a data set annually containing the percentage of bachelor's degrees granted to women from 1970 to 2012. The data set is broken up into 17 categories of degrees, with each column as a separate category. Randal Olson, a data scientist at University of Pennsylvania, has cleaned the data set and made it available on his personal website.

graduate_job_outcomes

In this project, I will be working with a dataset on the job outcomes of students who graduated from college between 2010 and 2012.

hacker_news

In this project we will be analysising data on the site in order to decipher which hours should you create a post to have a higher chance of receiving comments and what type do those posts fall under.

investigating_fandango_movie_ratings

In this project, we'll analyze more recent movie ratings data to determine whether there has been any change in Fandango's rating system after Hickey's analysis.

llama_api_qa_app

This application connects to an LLM via an api, a question-answering chatbot powered by the LLAMA model. Users ask questions about the content of the already installed file 'three_little_pigs.txt', and receive answers. The tool leverages LLAMA embeddings for efficient text processing. The LLM used is "llama-2-7b-chat.Q4_K_M.gguf" found here

llama_gradio_qa_app

This application implements a question-answering chatbot powered by the LLAMA model. Users can upload documents, ask questions about their content, and receive answers. The tool leverages LLAMA embeddings for efficient text processing and offers a user-friendly interface powered by Gradio. The LLM used is "llama-2-7b-chat.Q4_K_M.gguf" found here

mobile_app_for_lottery_addiction

A medical institute that aims to prevent and treat gambling addictions wants to build a dedicated mobile app to help lottery addicts better estimate their chances of winning. The institute has a team of engineers that will build the app, The goal of this project is to create the logical core of the app and calculate probabilities.

news_classifier_api

popular_data_science_questions

Using Data Science Stack Exchange, the goal of this project is to determine the best content to create for a data science company based on interest by subject.

predicting_bike_rentals

In this project, we'll try to predict the total number of bikes people rented in a given hour. We'll predict the cnt column using all of the other columns, except for casual and registered. To accomplish this, we'll create a few different machine learning models and evaluate their performance.

predicting_car_prices

In this project, we will be using machine learning workflow to predict a car's market price using its attributes.

predicting_house_sale_prices

In this project, we will work with housing data for the city of Ames, Iowa, United States from 2006 to 2010 to predict house sale prices using machine learning

predicting_the_stock_market

In this project, we'll be working with data from the S&P500 Index. We'll be using historical data on the price of the S&P500 Index to make predictions about future prices. Predicting whether an index will go up or down will help us forecast how the stock market as a whole will perform.

star_wars

This project, you'll be cleaning and exploring a data set regarding films in the Star Wars franchise.

top_mangas

MyAnimeList Dashboard

video_game_data

Analysis of video game data using Python, Pandas and Jupyter Notebook

winning_jeopardy

In this project, we'll work with a dataset of Jeopardy questions to figure out some patterns in the questions that could help you win.