Search result for Machine learning and linear algebra Online Courses & Certifications
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Quantum Machine Learning
by Peter Wittek- 0.0
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9 Weeks
Machine learning is a good candidate. In this course we will introduce several quantum machine learning algorithms and implement them in Python. Perform discrete optimization in ensembles and unsupervised machine learning with different quantum computing paradigms. Experiment with unusual kernel functions on quantum computers4) Demonstrate coherent quantum machine learning protocols and estimate their resources requirements....
$49
Machine Learning With Big Data
by Mai Nguyen , Ilkay Altintas- 4.6
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Approx. 22 hours to complete
This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. Goals and Activities in the Machine Learning Process Slides: Machine Learning Overview and Applications...
Developing AI Applications on Azure
by Ronald J. Daskevich, DCS- 4.4
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Approx. 16 hours to complete
We'll discuss machine learning types and tasks, and machine learning algorithms. Using the Azure Machine Learning Service you'll create and use an Azure Machine Learning Worksace. By the end of this course, you will be able to create, implement and deploy machine learning models. Definition of AI and Machine Learning Azure Machine Learning Service: Model Management and Deployment...
Fundamentals of Machine Learning in Finance
by Igor Halperin- 3.8
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Approx. 18 hours to complete
A learner with some or no previous knowledge of Machine Learning (ML) will get to know main algorithms of Supervised and Unsupervised Learning, and Reinforcement Learning, and will be able to use ML open source Python packages to design, test, and implement ML algorithms in Finance. Geron, “Hands-On Machine Learning with Scikit-Learn and TensorFlow”, Chapters 6 & 7...
AI Workflow: AI in Production
by Mark J Grover , Ray Lopez, Ph.D.- 4.5
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Approx. 17 hours to complete
Use IBM Watson OpenScale to assess bias and performance of production machine learning models. This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. Security and Machine Learning Models Review of Course 4: Machine Learning, Visual Recognition, and NLP...
Ordinary Differential Equations and Linear Algebra - Part 1
by Betul Orcan-Ekmekci- 0.0
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7 Weeks
, solutions to separable and linear first-order equations and to higher-order linear equations with constant coefficients, systems of linear differential equations, the properties of solutions to differential equations) and linear algebra (e. This course provides a comprehensive qualitative and quantitative analysis of ordinary differential equations and linear algebra. Linear Algebra: Matrix Algebra...
$169
Ordinary Differential Equations and Linear Algebra - Part 2
by Betul Orcan-Ekmekci- 0.0
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7 Weeks
, solutions to separable and linear first-order equations and to higher-order linear equations with constant coefficients, systems of linear differential equations, the properties of solutions to differential equations) and linear algebra (e. This course provides a comprehensive qualitative and quantitative analysis of ordinary differential equations and linear algebra. The first part focuses on 1st order differential equations and linear algebra....
$169
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Supervised Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
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Approx. 11 hours to complete
This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting. To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....
Supervised Machine Learning: Classification
by Mark J Grover , Miguel Maldonado- 4.9
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Approx. 11 hours to complete
This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting. To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....
Deep Learning and Reinforcement Learning
by Mark J Grover , Miguel Maldonado- 4.7
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Approx. 14 hours to complete
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis....
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