- Learn this important subset of artificial intelligence (AI)
- Free tutorial
- Rating: 3.9 out of 53.9 (18 ratings)
- 1,293 students
- 1hr 50min of on-demand video
- Created by Cloud Institute
English
What you’ll learn
- Understand the formulation of well-specified machine learning problems.
- Learn how to perform supervised and reinforcement learning, with images and temporal sequences.
- Linear Regression
- Gradient Descent
- Genetic Algorithms
Requirements
- Computer programming (python); Calculus; Linear Algebra
Description
This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptron’s, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with Python, open-source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, Coca Cola, eBay, Snapchat, Uber, and many more).
Course Objectives:
- Understand the formulation of well-specified machine learning problems.
- Learn how to perform supervised and reinforcement learning, with images and temporal sequences.
- Overview: AI and Machine Learning
- Linear Regression
- Gradient Descent
- Genetic Algorithms
About Cloud Institute:
Cloud Institute empowers teams with the cloud skills and knowledge needed to get the job done. Whether you need to hire, train, and deploy to build a work-ready talent pipeline, reskill and redeploy your workforce for hard-to-fill roles, continuously upskill your existing staff in cloud technologies, or immersive high-impact certification training specifically for your project and project success, Cloud Institute can help.
Who this course is for:
- Anyone with an IT background looking for a foundational understanding of machine learning models (logistic regression, multilayer perceptron’s, convolutional neural networks, natural language processing, etc.) as well as how these models can solve complex problems in a variety of industries.
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Course content
5 sections • 6 lectures • 1h 50m total lengthCollapse all sections
Introduction1 lecture • 7min
- Introduction07:01
Overview: AI and Machine Learning1 lecture • 57min
- Overview: AI and Machine Learning57:00
Linear Regression and Loss Functions1 lecture • 17min
- Linear Regression and Loss Functions16:40
Gradient Descent1 lecture • 17min
- Gradient Descent17:03
Genetic Algorithms2 lectures • 12min
- Genetic Algorithms11:40
- Thank You!00:47
