intermediate Python • beginner scikit-learn • beginner TensorFlow • basics of OpenCV and NumPy
skills learned
identify when to use classical machine learning algorithms or deep learning for classification • build a neural network architecture and automate the search for parameters
In this liveProject, you’ll step into the role of a developer working for car rental company CarsUnlimited. You have a bold new idea for an app that can revolutionize your business. You envisage a service where a customer can snap a picture of any car on the street, and instantly find out if CarsUnlimited has that make and model available. Your colleagues have the app UI covered; your challenge is to build the algorithm to classify the cars that were snapped by the user. You decide to develop a machine learning algorithm for solving this problem.
You’ll start with cleaning your data, before experimenting with classical machine learning algorithms such as SVMs, Random Forests, Decision Trees, and assess their performance metrics. With an entire range of parameters to tune and improve, you will learn about how to automate this search. From there, you’ll dive into building a deep neural network and explore different search strategies to finalize your powerful new neural network architecture.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
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project author
Karthik Muthuswamy
Dr. Karthik Muthuswamy works as a Senior Data Scientist for the AI Business Services team at SAP in Germany. He works on research and development of services that leverage machine learning to enable building Intelligent Enterprise applications and, is an active proponent of human-centered machine learning. He has created and delivered two openSAP courses on machine learning which teaches the nuances of using machine learning in enterprise settings.
Karthik was amongst the first Google Developer Experts for Machine Learning. He has used machine learning for developing applications such as guiding autonomous vehicles, sentence comprehending bots, among many others. He gives talks and conducts workshops on machine learning for the developer community to reduce the barriers of entry to developing applications that use machine learning and is an active contributor to open-source software.
prerequisites
This liveProject is for beginners to machine learning who have some existing knowledge of Python and linear algebra. To begin this liveProject, you will need to be familiar with:
TOOLS
Intermediate Python
Basics of Jupyter Notebook
Basics of scikit-learn and Autosklearn
Basics of TensorFlow, Tensorboard and Keras Tuner
TECHNIQUES
Basics of linear algebra
features
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