Machine Learning Fundamentals with Python

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Learn Path Description

Machine learning is changing the world and if you want to be a part of the ML revolution, this is a great place to start! In this track, you’ll learn the fundamental concepts in Machine Learning. 

Skills You Will Gain

Courses In This Learning Path

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Supervised Learning with scikit-learn

Machine learning refers to the science of teaching computers and machines how to use data from the past to predict future data. What is the best way to determine if a tumor is benign or not? Which customers will transfer their business to another company. Is this spam mail? This course will show you how to use Python to do machine learning's most important component, supervisedlearning. You'll be able to demonstrate how predictive models can built and tuned using real data. Scikit-learn, one of the most popular machine-learning libraries for Python, is very user-friendly.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Unsupervised Learning in Python

Imagine that you have customers with different characteristics. For example, their location, age and financial history. You need to identify patterns and group them together. A collection of text, such as Wikipedia pages, might be available that you wish to organize into different categories according their content. Unsupervised learning refers to unsupervised learning. Unsupervised learning is the absence of supervision or guidance in pattern discovery via a prediction task. Instead, you discover hidden structures using unlabeled data. Unsupervised learning can be used to many machine learning techniques including clustering, matrix factorization, dimension reduction, and matrix factorization. This course will cover the basics of unsupervised learning and how to implement the most critical algorithms using scikit-learn/scipy. This course will show you how to analyse, cluster, transform and visualize unlabeled data, as well as extract insights. This course also contains a recommendation system, which can be used for recommending musical artists.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Linear Classifiers in Python

This course will show you how scikit-learn can be used to teach linear classifiers. Once you've learned how to use these methods you can dive into their ideas to discover what makes them tick. This course will show you how to tune and train these Python linear classifiers. This course will also help you understand other machine learning algorithms.

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Total Duration

4 hours

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Level

Intermediate

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Learn Type

Certifications

Case Study: School Budgeting with Machine Learning in Python

Data science is not only useful for predicting ad clicks but also helps to make a social impact. This is a case study from a Machine Learning Competition at DrivenData. This course will address a problem that impacts school district budgeting. Schools can compare their spending with other schools easier by creating a model which automatically classifies items in school budgets. This course will show you how to create a basic model. Natural language processing will be taught to help you prepare modeling budgets. Next, you will need to compare your methods to other contestants. The winner is the person who can combine multiple expert techniques to create the best model.

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Total Duration

4 hours

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Level

Beginner

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Learn Type

Certifications

Introduction to Deep Learning in Python

Deep learning is a powerful machine-learning technique that has revolutionized various fields, including robotics and natural language processing. One example of its potential is seen in AlphaGo. For individuals interested in exploring this exciting technology, this course offers a hands-on experience in deep learning using Keras 2.0. Keras 2.0 is the latest version of a Python library specifically designed for deep learning. By enrolling in this course, participants will gain practical knowledge and skills in deep machine learning, as well as the ability to use Python for machine learning purposes. The course will cover the fundamentals of neural networks in machine learning using Python and introduce learners to important algorithms used in deep learning. Whether you are new to machine learning or already have some background, this course provides a comprehensive introduction to the field and offers opportunities for further growth and development. By the end of the course, participants will have a solid understanding of machine learning concepts and be able to apply them using Python programming. This course is perfect for those who want to learn about both machine learning and deep learning, providing a solid foundation for future studies or career opportunities in these areas. So don't miss out on this chance to jumpstart your journey into the exciting world of machine learning using Python!

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Total Duration

20 hours

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Level

Beginner

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Learn Type

Certifications

Machine Learning Fundamentals with Python

Machine learning is revolutionizing the world. This track is a great place for you to begin if your goal is to become a part the ML revolution! This track will teach you the basics of Machine Learning.

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