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Understanding Machine Learning with Python

Jerry Kurata
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Machine Learning Python Model Development scikit-learn Algorithms Data Preparation Prediction

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Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on practice with scikit-learn, a highly reputable library
Taught by Jerry Kurata, a respected instructor in the field
Introduces learners to major topics in Machine Learning
Builds a strong foundation for learners who are new to Machine Learning
Covers core skills and knowledge required for Machine Learning practice
Requires familiarity with basic software development and statistics

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Career center

Learners who complete Understanding Machine Learning with Python will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers use their knowledge of programming and data science to design, develop, and deploy machine learning models. This course can help you build a foundation in machine learning, which is essential for success in this role. You will learn how to prepare data, select algorithms, and evaluate models. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Machine Learning Engineer
Data Scientist
Data Scientists use their skills in statistics, programming, and data analysis to extract insights from data. This course can help you build a foundation in machine learning, which is a key skill for Data Scientists. You will learn how to use machine learning algorithms to solve real-world problems. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Data Scientist
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help you build a foundation in machine learning, which is becoming increasingly important in software development. You will learn how to use machine learning algorithms to solve problems such as fraud detection and customer segmentation. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Software Engineer
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can help you build a foundation in machine learning, which is becoming increasingly important in quantitative finance. You will learn how to use machine learning algorithms to solve problems such as risk management and portfolio optimization. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Quantitative Analyst
Business Analyst
Business Analysts use data to solve business problems. This course can help you build a foundation in machine learning, which is becoming increasingly important in business analysis. You will learn how to use machine learning algorithms to solve problems such as customer churn and fraud detection. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Business Analyst
Data Analyst
Data Analysts use data to extract insights and solve problems. This course can help you build a foundation in machine learning, which is becoming increasingly important in data analysis. You will learn how to use machine learning algorithms to solve problems such as customer segmentation and fraud detection. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Data Analyst
Statistician
Statisticians use data to solve problems and make predictions. This course can help you build a foundation in machine learning, which is becoming increasingly important in statistics. You will learn how to use machine learning algorithms to solve problems such as regression analysis and classification. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Statistician
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve problems in business and industry. This course can help you build a foundation in machine learning, which is becoming increasingly important in operations research. You will learn how to use machine learning algorithms to solve problems such as logistics and scheduling. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Operations Research Analyst
Financial Analyst
Financial Analysts use data to analyze financial markets and make investment recommendations. This course can help you build a foundation in machine learning, which is becoming increasingly important in financial analysis. You will learn how to use machine learning algorithms to solve problems such as stock price prediction and portfolio optimization. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Financial Analyst
Actuary
Actuaries use mathematical and statistical models to assess risk. This course can help you build a foundation in machine learning, which is becoming increasingly important in actuarial science. You will learn how to use machine learning algorithms to solve problems such as insurance pricing and risk management. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Actuary
Market Researcher
Market Researchers use data to understand consumer behavior. This course can help you build a foundation in machine learning, which is becoming increasingly important in market research. You will learn how to use machine learning algorithms to solve problems such as customer segmentation and product development. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Market Researcher
Product Manager
Product Managers use data to develop and launch new products. This course can help you build a foundation in machine learning, which is becoming increasingly important in product management. You will learn how to use machine learning algorithms to solve problems such as customer segmentation and product development. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Product Manager
Consultant
Consultants use data to help businesses solve problems. This course can help you build a foundation in machine learning, which is becoming increasingly important in consulting. You will learn how to use machine learning algorithms to solve problems such as customer segmentation and fraud detection. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Consultant
Teacher
Teachers use data to help students learn. This course can help you build a foundation in machine learning, which is becoming increasingly important in education. You will learn how to use machine learning algorithms to solve problems such as student assessment and personalized learning. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Teacher
Researcher
Researchers use data to solve problems and make discoveries. This course can help you build a foundation in machine learning, which is becoming increasingly important in research. You will learn how to use machine learning algorithms to solve problems such as data analysis and predictive modeling. This course will also help you develop the skills you need to work with the scikit-learn library, which is a popular tool for machine learning in Python.
See salaries and explore the career path for Researcher

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Understanding Machine Learning with Python.
Cover image
Deep Learning
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Provides a comprehensive overview of deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It good resource for learners who want to learn more about deep learning.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Information Theory, Inference and Learning...
Save
Provides a comprehensive overview of information theory, inference, and learning algorithms, covering topics such as entropy, mutual information, and Bayesian inference. It good resource for learners who want to learn more about the theoretical foundations of machine learning.
Information Theory, Inference and Learning...
Hardcover
$$$
Cover image
Probabilistic Machine Learning
Save
Provides a probabilistic perspective on machine learning, covering topics such as Bayesian inference, graphical models, and reinforcement learning. It good resource for learners who want to understand the theoretical foundations of machine learning.
Probabilistic Machine Learning: Advanced Topics...
Hardcover
$$$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a practical introduction to machine learning with Python, using the scikit-learn, Keras, and TensorFlow libraries. It good resource for learners who have some experience with Python and want to learn more about machine learning.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Deep Learning
Save
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as supervised and unsupervised learning, neural networks, and support vector machines. It good resource for learners who want to learn more about pattern recognition and machine learning.
Deep Learning: Foundations and Concepts
Hardcover
$$$
Cover image
Python Machine Learning
Save
Provides a comprehensive introduction to machine learning with Python, covering topics such as data preprocessing, model selection, and evaluation. It good resource for learners who are new to machine learning or Python.
Machine Learning with PyTorch and Scikit-Learn:...
Paperback
$$
Python Machine Learning: Machine Learning and Deep...
Paperback
$$
Python Machine Learning - Second Edition: Machine...
Paperback
$$
(Italiano) Machine Learning con Python - Nuova edizione:...
Kindle Edition
$$
(Deutsch) Machine Learning mit Python und Keras, TensorFlow 2...
Kindle Edition
$$
(Español) Machine Learning con PyTorch y Scikit-Learn:...
Paperback
$$$
(Español) Python Machine Learning
Paperback
$$
Cover image
Introduction to Machine Learning, fourth edition
Save
Provides a comprehensive overview of machine learning, covering topics such as supervised and unsupervised learning, deep learning, and reinforcement learning. It good resource for learners who want to learn more about machine learning.
Introduction to Machine Learning, fourth edition
Paperback
Check
Introduction to Machine Learning, fourth edition
Kindle Edition
Check
Cover image
Machine Learning Q and AI
Save
Provides a comprehensive overview of machine learning with Python, covering topics such as supervised and unsupervised learning, natural language processing, and computer vision. It good resource for learners who have some experience with Python and want to learn more about machine learning.
Machine Learning Q and AI: 30 Essential Questions...
Paperback
$$
Machine Learning Q and AI: 30 Essential Questions...
Kindle Edition
$$
Cover image
Statistical Learning with Sparsity
Save
Provides a comprehensive overview of sparse modeling, covering topics such as the lasso, elastic net, and group lasso. It good resource for learners who want to learn more about sparse modeling.
Statistical Learning with Sparsity: The Lasso and...
Paperback
$$
Cover image
Machine Learning for Hackers
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Provides a hands-on introduction to machine learning for hackers, covering topics such as data preprocessing, model selection, and evaluation. It good resource for learners who want to learn more about machine learning.
Machine Learning for Hackers: Case Studies and...
Paperback
$$
Machine Learning for Hackers: Case Studies and...
Kindle Edition
$$

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Time
1 hours
Via
Pluralsight
Instructor
Jerry Kurata
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides hands-on practice with scikit-learn, a highly reputable library
Taught by Jerry Kurata, a respected instructor in the field
Introduces learners to major topics in Machine Learning
Builds a strong foundation for learners who are new to Machine Learning
Covers core skills and knowledge required for Machine Learning practice
Requires familiarity with basic software development and statistics
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