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Steffano Mendes
@steffanobrito
Thiago Gadelha
@thiagogadelhaa
Fernando Trinta
@famt
Emanuele Santos
@emanueles
Jose Macedo
@josemacedo
Top Repositories
Aluminio
Repository for studies and implementation of design patterns in C++
Final project of the Database Fundamentals course at UFC (CK0114)
CPP course -> Basics and Advanced Topics
In this challenge, We need o create a machine learning model that will classify SMS messages as either "ham" or "spam". A "ham" message is a normal message sent by a friend. A "spam" message is an advertisement or a message sent by a company.
In this challenge, you will predict healthcare costs using a neural network. You are given a dataset that contains information about different people including their healthcare costs. Use the data to predict healthcare costs based on new data.
In this challenge, you will create a book recommendation algorithm using K-Nearest Neighbors. You will use the Book-Crossings dataset. This dataset contains 1.1 million ratings (scale of 1-10) of 270,000 books by 90,000 users.
Code to classify images of dogs and cats. Using TensorFlow 2.0 and Keras to create a convolutional neural network that correctly classifies images of cats and dogs at least 63% of the time. (Extra credit if you get it to 70% accuracy!)
Challenge: Create a program to play Rock, Paper, Scissors. A program that picks at random will usually win 50% of the time. To pass this challenge, the program must play matches against four different bots, winning at least 60% of the games in each match. The program is on RPS.py
Repository for the Machine Learning and Neural Networks course using TensorFlow.
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