Search result for Machine learning and linear algebra Online Courses & Certifications
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Machine Learning with Remote Sensing Data
by Spatial eLearning- 4.1
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1.5 hours on-demand video
Do you want to master machine learning algorithms to predict Earth Observation big data? In this Machine Learning with Earth Engine API course, I will help you get up and running on the Google Earth Engine cloud platform. Then you will apply various machine learning algorithms including linear regression, clustering, CART, and random forests....
$11.99
Data Manipulation at Scale: Systems and Algorithms
by Bill Howe- 4.3
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Approx. 20 hours to complete
Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields. Relational Databases and the Relational Algebra Relational Algebra and Datalog for Graphs...
Machine Learning: Regression
by Emily Fox , Carlos Guestrin- 4.8
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Approx. 22 hours to complete
In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. Important Update regarding the Machine Learning Specialization...
Prediction and Control with Function Approximation
by Martha White , Adam White- 4.8
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Approx. 22 hours to complete
You will see that estimating value functions can be cast as a supervised learning problem---function approximation---allowing you to build agents that carefully balance generalization and discrimination in order to maximize reward. You will learn about feature construction techniques for RL, and representation learning via neural networks and backprop. Read Me: Pre-requisites and Learning Objectives...
Machine Learning- Step by Step from basic to advanced level.
by EdYoda Digital University- 4.2
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7 hours on-demand video
Linear Models, Trees & Preprocessing in machine learning As a Machine Learning Engineer, you will work on real-life challenges and develop solutions that have a deep impact on how businesses and people thrive. 4) An exponential career graph – All said and done, Machine learning is still in its nascent stage....
$12.99
Neural Networks and Deep Learning
by Andrew NgTop Instructor , Kian KatanforooshTop Instructor , Younes Bensouda MourriTop Instructor- 4.9
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Approx. 23 hours to complete
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....
Data Science A-Z : Machine Learning with Python & R
by Arpan Gupta- 4.1
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12.5 hours on-demand video
Students who have at least high school knowledge in math and who want to start learning Machine Learning. Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning....
$12.99
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Mastering Data Science and Machine Learning Fundamentals
by AI Sciences- 4.2
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2 hours on-demand video
A comprehensive course that will teach you how Data Science and Machine Learning Work. Data Science and Machine learning is not just another buzzword. The course not only guides you through the problems and concepts of machine learning but also elaborates on how to implement those concepts successfully. Basics of Machine Learning...
$9.99
Computer Vision Basics
by Radhakrishna Dasari , Junsong Yuan- 4.2
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Approx. 13 hours to complete
They are equipped to identify some key application areas of computer vision and understand the digital imaging process. Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). Linear Algebra...
Applied Data Science for Data Analysts
by Kevin Coyle , Mark Roepke , Emma Freeman- 4.2
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Approx. 16 hours to complete
You'll work through the data science process to and use unsupervised learning to explore data, engineer and select meaningful features, and solve complex supervised learning problems using tree-based models. Review of Machine Learning Machine Learning Workflow Linear Regression Coefficients and P-values Label Imbalance and Sampling Model Generalization and Validation Set Explore data using unsupervised machine learning....
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