Machine learning techniques are divided to classic machine learning techniques and contemporary ones (deep learning). These artificial Intelligence techniques are used to learn and infer from data and build computational models. Every day, we live with Machine Learning algorithms intertwining with our daily lives: Spam Filtering; Web Search; Postal Mail Routing; Fraud Detection; Movie Recommendations; Vehicle Driver Assistance; Web Advertisements; Social Networks and Speech Recognition. So it is important to know what are these techniques and when do we need them to apply?
You will be provided with the grand tour of machine learning and deep learning case scenarios for business. You will learn essential skills in Machine Learning and Deep Learning in Python as well as methodology for training machines. Included in this course is math for grown-ups, an introduction to programming Python. It also includes instructions on how to manage, visualize and analyze your data as well as providing lessons on building, validating and tuning your models. In addition to all the theory there will be a lot practice in the form of several exercise projects. By the end of this course, you will be familiar with the business opportunity of machine learning to unlock immense value in every day technology breakthroughs.
Students will also be given hands on experience as well through being taught the different types of problem-solving scenarios for Machine Learning and several examples of Deep Learning, including:
1. Overview of Machine Learning
- Supervised and Unsupervised Learning
2. Overview of Classic Machine Learning Techniques
- Use Cases for Machine Learning
- Tools for Machine Learning
3. Overview of Deep Learning Techniques
- Use Cases for Deep Learning
- Data for Deep Learning
- Tools for Deep Learning
- Computer Visions Models (CNNs)
This is a Premium New Horizons course. This course usually runs in a connected classroom, and students need to bring their own device.
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