Learn Machine Learning By Building Projects

  Project 1 - Breast Cancer Detection - In this project, you will use the K-nearest neighbor algorithm to help detect breast cancer malignancies by using a support vector machine.

  Project 2 - Board Game Review - You will learn how to perform a linear regression analysis by predicting the average reviews on a board game in this project.

  Project 3 - Credit Card Fraud Detection - In this project, you are going to do a credit card fraud detection and going to focus on anomaly detection by using probability densities.

  Project 4 - Stock Market Clustering Project - In this project, you will use a K-means clustering algorithm to identify related companies by finding correlations among stock market movements over a given time span.

  Project 5 - Diabetes Onset Detection - In this project, you will fine-tune a deep learning neural network by performing a grid search to detect the onset of diabetes based on patient data.

  Project 6 - Markov Models and K-Nearest Neighbor Approaches to Classifying DNA Sequences - In this project, you will learn about bioinformatics by using Markov models and K-nearest neighbor (KNN) algorithms to classify E. Coli DNA sequences.

  Project 7 - Getting Started with Natural Language Processing In Python - This project will cover Natural Language Processing (NLP) methodology, including tokenizing words and sentences, part of speech identification and tagging, and phrase chunking.

  Project 8 - Obtaining Near State-of-the-Art Performance on Object Recognition Tasks Using Deep Learning - This project will use the CIFAR-10 object recognition dataset as a benchmark and will implement a recently published deep neural network that can obtain similar results to state-of-the-art networks.

  Project 9 - Image Super Resolution with the SRCNN - In this tutorial, we will implement and use a Tensorflow version of the Super Resolution Convolutional Neural Network (SRCNN) to improve the image quality of degraded images.

  Project 10 - Natural Language Processing: Text Classification - This project will take an advance approach to Natural Language Processing by solving a text classification task using multiple classification algorithms, including a Naive Bayes classifier, SGD classifier, and linear support vector classifier (SVC). So, what are you waiting for? Become a machine learning magician with this extensive course!

  Project 11 - K-Means Clustering For Image Analysis - In this project, you will 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 12 - Data Compression & Visualization Using Principle Component Analysis - 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.

 Section 1 : Breast Cancer Detection

 Section 2 : Board Game Review Prediction

 Section 3 : Credit Card Fraud Detection

 Section 4 : Stock Market Clustering

 Section 5 : Diabetes Onset Detection

 Section 6 : DNA Classification - The Dataset

 Section 7 : Intro to Natural Language Processing

 Section 8 : Object Recognition

 Section 9 : Image Super Resolution

 Section 10 : Text Classification

 Section 11 : KMeans

 Section 12 : PCA