Projects
Project: Recognize hand written digits
Project: Recognize hand written digits
We'll develop and train a machine learning model to recognize hand written digits.
We'll develop and train a machine learning model to recognize hand written digits.
Level: Beginner (No prerequisite)
Level: Beginner (No prerequisite)
Team
Abraham Korssa, James Gonzalez , Rohin Dutt, Jeremy You, Apurva Mishra, Parmeshvar Prakash, Arielle Iosiv, Gavin House, Min Wang , Reilly Dowell, Aashi Soni, Neeleshmohan Mudalkar, Nikhil Mathew
Project: Predict Epidemic
Project: Predict Epidemic
Develop a regression model that predicts the next day's Epidemic in a country based on features such as population dynamics, location, previous epidemic cases, etc. Extensive data preprocessing techniques such as data cleansing, normalization, feature scaling, and dimensionality reduction (such as Principal Components Analysis) will be utilized.
Develop a regression model that predicts the next day's Epidemic in a country based on features such as population dynamics, location, previous epidemic cases, etc. Extensive data preprocessing techniques such as data cleansing, normalization, feature scaling, and dimensionality reduction (such as Principal Components Analysis) will be utilized.
Level: Intermediate / Advanced
Level: Intermediate / Advanced
Prerequisites: An understanding of basic Machine Learning Regression concepts (ex. linear and polynomial regression) and a working knowledge of Python and high school algebra. The ML camp conducted by Community AI is sufficient. Data Preprocessing techniques will be discussed in detail as we go along
Prerequisites: An understanding of basic Machine Learning Regression concepts (ex. linear and polynomial regression) and a working knowledge of Python and high school algebra. The ML camp conducted by Community AI is sufficient. Data Preprocessing techniques will be discussed in detail as we go along
Team
Richard Lian , Noah Stewart, Tanishk , Jash Pola, Sai Javvadi, Abhinav Reddy