In this project you'll make your own Connect Four AI and try to beat ours

Build Your Own Connect Four AI

Classify tumors as either malignant or benign using K-Nearest Neighbors.

Cancer Classifier

Get started with ChatGPT by writing a short story!

ChatGPT as a Creative Writing Assistant

Practice ChatGPT prompt engineering while learning a new language!

ChatGPT for Learning a New Language

In this project, you will create a neural network that classifies mortality due to heart disease.

Classification

Build a deep learning model with TensorFlow to detect and classify infections from real X-ray scans.

Classify X-rays With Machine Learning

In this project, you will use a Convolutional Neural Network (CNN) to classify galaxies.

Classifying Galaxies

Fine-tune pre-trained BERT transformers from Hugging Face in PyTorch to classify IMDB movie reviews.

Classifying IMDB Movie Reviews with BERT Transformers

Train and evaluate a CNN to detect tumors in histopathological scans from the PatchCamelyon dataset.

Classifying Microscopic Histopathology Images with PyTorch

Get started using generative AI by illustrating a children's book!

Create a Children's Picture Book Using Midjourney

You will create a regression deep learning model that predicts an applicant's graduate admissions chances based on various parameters, such as grades, test scores, and program rating.

Deep Learning Regression with Admissions Data

Perform a natural language parsing analysis with regular expressions to gain insights into Oscar Wilde's _The Picture of Dorian Gray_ or Homer's _The Iliad!_

Discover Insights into Classic Texts

In this project you will categorize emails using a Naive Bayes Classifier.

Email Similarity

Predicting employee attrition is challenging for HR departments, as it helps organizations retain valuable talent and reduce turnover costs. However, AI models used in such decisions must be transparent and interpretable, ensuring that HR professionals can trust and understand the predictions.

In this project, we will use the IBM HR Analytics Employee Attrition Dataset to predict whether an employee will likely leave the company. We will train different machine learning models and apply Explainable AI (XAI) techniques to interpret their predictions.

By the end of this project, we will have a fully interpretable pipeline that can help HR professionals make informed, fair, and data-driven decisions regarding employee retention.

Explainable AI in Employee Attrition Prediction

This project demonstrates how to use the LIME (Local Interpretable Model-agnostic Explanations) library to understand and explain predictions made by a machine learning model for breast cancer diagnosis. Using the Wisconsin Breast Cancer [dataset](https://archive.ics.uci.edu/dataset/17/breast+cancer+wisconsin+diagnostic), we analyze how individual features, such as mean radius, texture, and smoothness, influence the model's decision to classify a tumor as benign or malignant. By visualizing LIME values, we gain insights into the contribution of each feature to the model's predictions, enabling better transparency and trust in AI-driven healthcare diagnostics.

Explaining Breast Cancer Diagnosis Predictions with LIME

This project demonstrates how to use SHAP (SHapley Additive exPlanations) to interpret the predictions of a machine learning classification model for breast cancer diagnosis. Using the Wisconsin Breast Cancer [dataset](https://archive.ics.uci.edu/dataset/17/breast+cancer+wisconsin+diagnostic), we analyze how individual features, such as mean radius, texture, and smoothness, influence the model's decision to classify a tumor as benign or malignant. By visualizing SHAP values, we gain insights into the contribution of each feature to the model's predictions, enabling better transparency and trust in AI-driven healthcare diagnostics.

Explaining Breast Cancer Diagnosis Predictions with SHAP

Begin to grasp the environmental impact of transformer models by experimenting with decoders and the CodeCarbon emissions tracking library.

Exploring Transformers and their Carbon Footprint

Use decision trees to predict what continent a flag comes from based on features like color and shape.

Find the Flag

Create neural networks in PyTorch to generate text using Mary Shelley's novel Frankenstein.

Generating Text with Frankenstein Using PyTorch 

In this project, you will be using K-Means clustering and scikit-learn to cluster images of handwritten digits.

Handwriting Recognition using K-Means

In this project, you will design, train, and evaluate a neural network model performing the task of regression to predict the life expectancy of countries using this dataset using Python and TensorFlow!

Implementing Neural Networks

Create an AI-powered recipe creation application using JavaScript and the OpenAI API. Customize the recipe to offer personalized cooking suggestions based on user preferences, dietary restrictions, and ingredient availability. 

OpenAI JavaScript API: Recipe Blog 

Create an AI-powered recipe creation application using Python and the OpenAI API. Customize the recipe to offer personalized cooking suggestions based on user preferences, dietary restrictions, and ingredient availability. 

OpenAI Python API: Recipe Blog 

Train Perceptrons to work like logic gates! This simple neuron can act as an AND or an OR gate.

Perceptron Logic Gates

Use transformers to fine-tune a vision transfomer (ViT) for image classification and evaluate an object detection model (e.g., DETR) on the Oxford-IIIT Pet Dataset.

Pet Image Classification and Detection with Transformers

Use Logistic Regression to predict credit card fraud.

Predict Credit Card Fraud

Create a neural network in PyTorch to predict electric vehicle charging loads.

Predicting Electric Vehicle Charging Loads

Create a neural network in PyTorch to predict hotel cancellations.

Predicting Hotel Booking Cancellations

Use random forests to predict the income of a person based on census data.

Predicting Income with Random Forests

In this project you will use tf-idf to analyze a collection of news articles.

Read the News Analysis

Design a sentiment analyzer using your prompt engineering skills in this project.

Sentiment Analysis

In this project you will use word embeddings to analyze the inaugural addresses of the United States of America presidents.

U.S.A. Presidential Vocabulary

Get started using ChatGPT by planning a trip!

Use ChatGPT to Create an Itinerary

Define and build a calculator with Generative AI!

Using Generative AI to Code

Use Midjourney to create an ad-campaign for a product

Using Generative AI to Create an Ad Campaign

This project explores how to use generative AI to develop a marketing plan for launching a new app.

Practice projects in AI

Solidify concepts with guided practice.

Build Your Own Connect Four AI

Cancer Classifier

ChatGPT as a Creative Writing Assistant

ChatGPT for Learning a New Language

Classification

Classify X-rays With Machine Learning

Classifying Galaxies

Classifying IMDB Movie Reviews with BERT Transformers

Classifying Microscopic Histopathology Images with PyTorch

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