This repo holds all the challenge and mini projects from Codecademy, relating to the following courses:
- Python
- Data Science: Natural Language Processing
- Deep Learning with TensorFlow
- Machine Learning/ AI Engineering
- Data Scientist: Machine Learning
- Analyze Data with R
- Data Science: Inference Specialist
- Data Science: Analytics
- Data Science Foundations
- ML and AI Fundamentals
- Master Statistics with Python
- Fundamental Math for Data Science
- Analyze Data with Python
- Cleaning Data with Python
- Visualize Data with Python
- Software Engineerin for Data Scientists
- Software Engineering for Python
- Learn Statistics with Numpy
- Learn Python 3
- SQL
- Analyze Data with SQL
- Bash/ Terminal
- Learn Command Line
- Javascript
- Learn Javascript
| Category | Project Title | Description |
|---|---|---|
| Python - NLP | Presidential Speeches | Analyzing inaugural speeches to learn how they use language to convey their adgenda with Word Embedding |
| Python - NLP | News Analysis | Using tf-idf to analyze article contents and uncover the terms that best describe each article |
| Python - NLP | Predicting Mystery Postcard | Using NBC to predict which friend sent a mystery letter |
| Python - NLP | Discover Insights from Classic Texts | Noun Phrase Parsing and Verb Phrase Parsing to analyze classic texts |
| Python - Big Data with PySpark | Analyze Common Crawl Data with PySpark | Introduction to PySpark Queries and RDD |
| Python - Deep Learning | Classifying Galaxies with Conv Neural Networks | Using a dataset of 10000 (128x128, 3) images of galaxies, build a classification model to predict what type of galaxy the corrosponding image is. |
| Python - Deep Learniing | Deep Learning Classification with Heart Disease Data | Using a dataset from kaggle to predict the survival of patients with heart disease based on patient characteristics and serum panel |
| Python - Deep Learning | Deep Learning Regression with Admissions Data | Mini-project focused on building a deep learning regression model to predict college admission chance based on different features |
| Python - Deep Learning | Implementing Neural Networks | Utilizing a neural network to predict life expectancy using WHO Global Health data |
| Python - ML | Book Recommender | Using suprise library, building a recommendation algorithm for book readers |
| Python - ML | Perceptron | Using a perceptron to model after and, or and xor logic gates. |
| Python - OOP | School Catalog | Refresher on OOP |
| Python - ML - Pipelines | Building ML Pipelines | Using UCI's bone marrow data to build a pipeline including preprocessing, cleaning and selecting a classifier |
| Python - ML - Boosting | Predict whether an individual makes over $50K | Using Census Data, predicting if a person makes more than 50K annually |
| Python - ML - Random Forests | Predict whether an individual makes over $50K | Using Census Data, predicting if a person makes more than 50K annually |
| Python - ML - Hyperparameter Tuning | Classifying Raisins with Hyperparameter Tuning | Classifying different grain raisin types using Murat Koklu's Kaggle dataset |
| Python - ML - Logisitic Regression with CV | Predicting Wine Quality | Using data from UCI's Machine Learning Repository, predicting wine quality with regularization techniques with logisitc regression |
| Python - ML - Support Vector Machines | Predict Baseball Strikezones | Using a baseball dataset to find the decision boundary of a strikezone |
| Python - ML/NLP - Naive Bayes Classifier | Email Similarity | Using fetch_20_newsgroups dataset from sklearn.datasets, train a model to classifcy email types |
| Python - ML - KMC | Handwriting Recognition with KMeans Clustering | Using the digits library from sklearn.datasets, creating a kmeans clustering algo to predict handwriting |
| Python - ML - Wrapper Methods | Wrapper Methods | Determining which feature selection method improves the obesity prediction model |
| Python - ML - Decision Trees | Find the flag! | Generating decision trees using flag data |
| Python - ML - K Nearest Neighbors | Cancer Classifier | Using SkLearn's neighbors library, predict if a patient has breast cancer. |
| Python - ML - Linear Regression | Honey Production | Using SkLearn's Linear model library, predict the production output of honey by 2050. |
| Python - ML - Data Transformation | Transformating Data into Features | Transforming categorical data, scaling data, working with datetime features |
| R - ML | Predicting Income with Social Data | Using R to uncover how age, education and gender plays a role in income |
| Python - ML - Logistic Regression | Predicting Credit Card Fraud | Using Scikit-Learn LogisticRegression model to predict credit card fraud |
| Python - ML | Class Objects to Store Patient Information | Refresher on class objects and OOP |
| Python - Probability | True probability of coin flip | Visualizing the true probability of a coin flip |
| Data Analysis - BI | Intro to Tableau for Data Analysis | Learning to use Tableau to show the relationship between NYC trees and Income |
| Data Analysis, Visualization, Python | Roller Coasters | Visualizing different roller coasters using functions |
| Data Analysis and Visualization | Board Slides for FoodWheel | Tracking business insights and consumer insights |
| Visualization | Constellations | Mapping Orion star system |
| SQL - Engineering | First-Last-Touch-Attribution | Finding first/ last touch attribution through different media channels |
| SQL - Engineering | Calculating Churn Rates | Calculating Churn rate for a fictional company Codeflix |
| Data Analytics - AB Testing | Ad effectiveness with AB Testing | AB Testing for conversion rate |
| Data Visualization | Airline Trends | Visualizing airline trends |
| Data Analytics | NBA Trends | Analyze trends to explore associations between score, win rates, |
| Data Analytics - Exploratory Data Analysis | EDA: Diagnosing Diabetes | Analyze diagnostic factors that affect diabetic outcomes in patients |
| Data Analytics | Exploring Mushrooms | Summarizing nominal characteristics of mushrooms |
| Data Analytics | Analyzing Internet Use with Python | Analyzing internet usage rates across the world between 1990 and 2020 using aggregation techniques |
| Data Analytics - Usage Funnel | Page Visits Funnel | Merging complimentary datasets to determine the proportion of users that complete their purchses in a fictional t-shirt ecommerce website. |
| Data Analytics | Product Defects | Using distributions to predict the number of product defects in a given day. |
| Data Analytics | Analyzing High-Speed Railway Delays | Using EDA and aggregation methods, determining how weather impacts railway times. |
| Data Analytics | Summarizing Automobile Evaluation Data | Summarizing categorical data of cat manufacturers |
| Python - Concurrent Programming | Concurrent Programming | Learning concurrent programming |
| Data Analytics - Summaries | Analyze Electric Vehicle Stations in Python | Summarizing private and public charging stations in the US in Jupyter |
| Python - Context Manageres | Aisha’s Greetings | Using context managers and constructors to generate card messages |
| Python - Error Logging | ATM Logging | Error Logging practice |
| Python - Generators | Boredless Tourist | OOP Practice |
| Python - Classes and Constructors | Basta Faloozin | Constructor practice |
| Python - Basic Statistics | Crunchie Munchies | Basic statistics with numpy |
| Python - Basic Visualizations | Election Results | Basic data visualizations with pyplot |
| Python - Classes | School Catalogue | Practice with constructors and dunder methods |
| Python - Functions | Functional Programming | Learning how to write basic functions |
| Python - Functions | Scrabble | Learning basic function syntax |
| Python - Loops and conditional | Thread Shed | Practice with loops |
| Shell scripts | Building build script |