Search result for Machine learning and linear algebra Online Courses & Certifications
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Mathematics for Machine Learning: Linear Algebra
by David Dye , Samuel J. Cooper , A. Freddie Page- 4.7
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Approx. 19 hours to complete
At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning. Introduction to Linear Algebra and to Mathematics for Machine Learning Basis, vector space, and linear independence...
Guided Tour of Machine Learning in Finance
by Igor Halperin- 3.8
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Approx. 24 hours to complete
Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. Artificial Intelligence and Machine Learning, Part I Geron, “Hands-On Machine Learning with Scikit-Learn and TensorFlow”, Chapter 1...
Applied Machine Learning in Python
by Kevyn Collins-Thompson- 4.6
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Approx. 34 hours to complete
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. Key Concepts in Machine Learning...
Supervised Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.8
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Approx. 11 hours to complete
Differentiate uses and applications of classification and regression in the context of supervised machine learning This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Regression techniques in a business setting. Introduction to Supervised Machine Learning and Linear Regression Introduction to Supervised Machine Learning: Types of Machine Learning Supervised Machine Learning for Interpretation and Prediction...
Supervised Machine Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.7
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Approx. 11 hours to complete
Differentiate uses and applications of classification and regression in the context of supervised machine learning This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Regression techniques in a business setting. Introduction to Supervised Machine Learning and Linear Regression Introduction to Supervised Machine Learning: Types of Machine Learning Supervised Machine Learning for Interpretation and Prediction...
Mathematical Foundation For Machine Learning and AI
by Eduonix Learning Solutions- 4.4
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4.5 hours on-demand video
Learn the core mathematical concepts for machine learning and learn to implement them in R and python However, learning to write algorithms for AI and ML isn’t easy and mathematical theories: Linear Algebra, Multivariate Calculus and Algebra – Linear algebra notation is used in Machine Learning to describe the parameters and structure of different machine...
$9.99
Python Machine Learning : Learn Handson™
by Handson ™- 4.7
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7.5 hours on-demand video
After completion of this course students will understand and apply the concepts of machine learning and applied statistics for real world problems. Terminal competencies of the course, one would have learnt about tools to train machines based on real-world situations using Machine Learning algorithms, as well as to create complex algorithms and neural networks....
$12.99
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Mathematical Foundations of Machine Learning
by Dr Jon Krohn- 4.5
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15.5 hours on-demand video
Essential Linear Algebra and Calculus Hands-On in NumPy, TensorFlow, and PyTorch Jon Krohn, this course provides a firm grasp of the mathematics — namely the linear algebra and calculus — that underlies machine learning algorithms and data science models. Understand the fundamentals of linear algebra and calculus, critical mathematical subjects underlying all of machine learning and data science...
$17.99
Machine Learning with Python
by SAEED AGHABOZORGI , Joseph Santarcangelo- 4.7
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Approx. 21 hours to complete
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms....
Data Science for Business Innovation
by Marco Brambilla , Emanuele Della Valle- 4.2
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Approx. 7 hours to complete
Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues. It discusses the value that Data Science can create, the main classes of problems that Data Science can solve, the difference is between descriptive, predictive and prescriptive analytics, and the roles of machine learning and artificial intelligence....
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