This repository stores guided projects completed while learning data science concepts with Dataquest. I worked on a variety of projects using tools such as Python, SQL, Excel, and Power BI, practicing data cleaning, analysis, visualization, web scraping, and working with APIs, as well as data modeling and forecasting.
The primary data science libraries I used include Pandas, NumPy, Requests, BeautifulSoup, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, and Keras. In machine learning, I applied various regression, classification, and clustering algorithms (e.g. OLS, Ridge, Lasso, KNN, Decision Tree, K-Means). In deep learning, I focused on building neural networks using both the Sequential and Functional APIs.
If you'd like to work on any of the available projects, be sure to find and download the project files from the Datasets folder, which contains CSV, Data Base, and SQL Text files.