Skills Earned:

1.Supervised Learning

    Regression
    Perceptron Algorithms
    Decision Trees
    Naive Bayes
    Support Vector Machines
    Ensemble of Learners
    Evaluation Metrics
    Training and Tuning Models

2.Neural Networks

    Introduction to Neural Networks
    Implementing Gradient Descent
    Training Neural Networks
    Deep Learning with TensorFlow

3.Unsupervised Learning

    Clustering
    Hierarchical and Density-Based Clustering
    Gaussian Mixture Models
    Dimensionality Reduction

Projects:

1.Finding Donors for CharityML:

    Apply supervised learning techniques on data collected for the US census to help CharityML (a fictitious charity organization) identify groups of people that are most likely to donate to their cause.

2.Create Your Own Image Classifier:

    Define and train a neural network in TensorFlow that learns to classify images; going from image data exploration to network training and evaluation.

3.Identify Customer Segments with Arvato:

    Study a real dataset of customers for a company, and apply several unsupervised learning techniques in order to segment customers into similar groups and extract information that may be used for marketing or product improvement.