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Innovating with Data and Google Cloud
by Google Cloud Training- 4.9
Approx. 2 hours to complete
Module 3: Innovation with Machine Learning 03: Innovation with Machine Learning Identify Google Cloud’s solutions for Machine Learning and AI...
MongoDB Aggregation Framework
by Nathan Leniz , Kirby Kohlmorgen- 4.6
Approx. 19 hours to complete
This will lay the groundwork for the remainder of the course where you'll dive deep and learn about schema design, relational data migrations, and machine learning with Machine Learning with MongoDB Intro: Associative Role Learning Intro: Associative Role Learning...
Preparing for the Google Cloud Professional Data Engineer Exam
by Google Cloud Training- 4.6
Approx. 9 hours to complete
Operationalizing Machine Learning Models Machine learning Machine learning and unstructured data Operationalizing Machine Learning Models: Exam Guide Review Operationalizing Machine Learning Models...
MOOC and Blended Learning
by Shijie Yu- 0.0
Approx. 5 hours to complete
2 Learning Styles and Learning Types 3 Multimodal Data Analysis of Students' Learning Behaviors and Needs 5 Expanding Learning Time and Space and Promoting Deeper Learning 6 Autonomous Learning System Cases 6 Rain Classroom Solves the Learning Problem Before Class, in Class and After Class...
Blended Language Learning: Design and Practice for Teachers
by Edwige SimonTop Instructor- 4.8
Approx. 21 hours to complete
In the first module we are going to discuss the origins and effectiveness of the blended learning model. Explain blended learning as a teaching modality and discuss its effectiveness Select tools and technologies to support blended language learning How did Blended Learning Start? Building a Blended Learning Course (Unit Level Considerations) Blended Language Learning Assessments...
Data Science Fundamentals for Data Analysts
by Emma Freeman , Mark Roepke- 0.0
Approx. 19 hours to complete
Supervised and Unsupervised Learning Basics of Machine Learning Practical Machine Learning A Review of Supervised Learning and Regression Machine Learning Solutions Discussion Intro Machine Learning Solutions...
AI Workflow: Machine Learning, Visual Recognition and NLP
by Mark J Grover , Ray Lopez, Ph.D.- 4.5
Approx. 14 hours to complete
Explain the use of linear and logistic regression in supervised learning applications Explain the use of tree-based algorithms in supervised learning applications Explain the use of Neural Networks in supervised learning applications 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....
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Lazy Trading Part 6: Detect Market status with AI
by Vladimir Zhbanko- 4.5
3.5 hours on-demand video
Learn to use Supervised Deep Learning modelling to detect patterns of Financial Assets Manipulate data and learn to build Classification Deep Learning Models Learn using R to read, manipulate data and perform Machine Learning including Deep Learning Prepare Time-Series data for Deep Learning Tasks Detect Market Status of Financial Assets using Deep Learning...
$12.99
Art and Science of Machine Learning
by Google Cloud Training- 4.6
Approx. 19 hours to complete
You will learn how to generalize your model using Regularization techniques and about the effects of hyperparameters such as batch size and learning rate on model performance. Learning rate and batch size Lab Intro: Reviewing Learning Curves Tune batch size and learning rate for better model performance...
Grammar and Punctuation
by Tamy Chapman , Helen Nam , Brad Gilpin- 4.7
Approx. 17 hours to complete
Learning Objectives Learning Objectives Learning Objectives Learning Objectives Learning Objectives Learning Objectives Learning Objectives...