Projects
Project 1 -Board Game Review Prediction โ In this project, youโll see how to perform a linear regression analysis by predicting the average reviews on a board game in this project.
Project 2 โ Credit Card Fraud Detection โ In this project, youโll learn to focus on anomaly detection by using probability densities to detect credit card fraud.
Project 3 โ Stock Market Clustering โ Learn how to use the K-means clustering algorithm to find related companies by finding correlations among stock market movements over a given time span.
Project 4 โ Getting Started with Natural Language Processing In Python โ This project will focus on Natural Language Processing (NLP) methodology, such as tokenizing words and sentences, part of speech identification and tagging, and phrase chunking.
Project 5โ Obtaining Near State-of-the-Art Performance on Object Recognition Tasks Using Deep Learning โ In this project, will use the CIFAR-10 object recognition dataset as a benchmark to implement a recently published deep neural network.
Project 6 โ Image Super Resolution with the SRCNN โ Learn how to implement and use a Tensorflow version of the Super Resolution Convolutional Neural Network (SRCNN) for improving image quality.
Project 7 โ Natural Language Processing: Text Classification โ In this project, youโll learn an advanced approach to Natural Language
Processing by solving a text classification task using multiple classification algorithms.
Project 8 โ K-Means Clustering For Image Analysis โ In this project, youโll learn how to use K-Means clustering in an unsupervised
learning method to analyze and classify 28 x 28 pixel images from the MNIST dataset.
Project 9 โ Data Compression & Visualization Using Principle Component Analysis โ This project will show you how to compress our Iris dataset into a 2D feature set and how to visualize it through a normal x-y plot using k-means clustering.