Search result for Introduction to machine learning Online Courses & Certifications
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Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud
by Reza Farivar , Roy H. Campbell- 4.3
Approx. 20 hours to complete
Week four focuses on Graph Processing, Machine Learning, and Deep Learning. Then we move to machine learning with examples from Mahout and Spark. 1 Introduction to Distros 1 Introduction to MapReduce with Spark 5 Zookeeper and Paxos: Introduction 1 Cassandra Introduction Module 4: Graph Processing and Machine Learning 1 Big Data Machine Learning Introduction 9 Introduction to Deep Learning...
An Introduction to Practical Deep Learning
by Andres Rodriguez , Nikhil Murthy , Hanlin Tang- 4.3
Approx. 17 hours to complete
You will explore important concepts in Deep Learning, train deep networks using Intel Nervana Neon, apply Deep Learning to various applications and explore new and emerging Deep Learning topics. Introduction to Deep Learning and Deep Learning Basics Introduction to Deep Learning Exercise 1: Introduction to Deep Learning Introduction to Deep Learning and Deep Learning Basics...
Introduction to Machine Learning in R
by Holczer Balazs- 4
8 hours on-demand video
Machine learning, neural networks, regression, SVM, naive bayes classifier, bagging, boosting, random forest classifier This course is about the fundamental concepts of machine learning, facusing on neural networks. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. machine learning basics...
$12.99
Introduction to Machine Learning in Production
by Andrew NgTop Instructor , Cristian Bartolomé ArámburuTop Instructor- 4.8
Approx. 10 hours to complete
In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype the process for developing, deploying, and continuously improving a productionized ML application....
Data Science Project: MATLAB for the Real World
by Michael Reardon , Brandon Armstrong , Erin Byrne , Adam Filion , Heather Gorr , Maria Gavilan-Alfonso , Matt Rich , Isaac Bruss- 4.8
Approx. 13 hours to complete
In the capstone project, you will apply the skills learned across courses in the Practical Data Science with MATLAB specialization to explore, process, analyze, and model data. Instructor Introduction Introduction to the Capstone Project Introduction to Module 2 Apply Machine Learning Introduction to Module 3 Introduction to Module 4...
Machine Learning Using SAS Viya
by Jeff Thompson , Catherine Truxillo- 4.7
Approx. 35 hours to complete
This course covers the theoretical foundation for different techniques associated with supervised machine learning models. You learn to train supervised machine learning models to make better decisions on big data. Getting Started with Machine Learning using SAS® Viya® Machine Learning in SAS Viya Regularizing and Tuning the Hyperparameters of a Machine Learning Model...
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
by Laurence Moroney- 4.7
Approx. 30 hours to complete
This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. Introduction to Google Colaboratory Introduction to Computer Vision...
Design Thinking and Predictive Analytics for Data Products
by Julian McAuley , Ilkay Altintas- 4.5
Approx. 8 hours to complete
In this course, you will understand the fundamental concepts of statistical learning and learn various methods of building predictive models. Week 1: Supervised Learning & Regression Introduction to Supervised Learning Review: Supervised Learning Supervised Learning & Regression Introduction to Support Vector Machines Introduction to Training and Testing Where to Find Datasets...
Blended Learning: Personalizing Education for Students
by Brian Greenberg , Rob Schwartz , Michael Horn- 4.8
Approx. 9 hours to complete
- The role of the student and how to support students in the transition from traditional to blended learning If you are interested in learning more about how to best leverage technology in education and rethink the way we run schools, join this MOOC and encourage your colleagues to do the same. Introduction and Blended Learning Models...
AWS Computer Vision: Getting Started with GluonCV
by Thom LaneTop Instructor , Thomas DelteilTop Instructor , Soji AdeshinaTop Instructor- 4.6
Approx. 31 hours to complete
This course provides an overview of Computer Vision (CV), Machine Learning (ML) with Amazon Web Services (AWS), and how to build and train a CV model using the Apache MXNet and GluonCV toolkit. Module 1: Introduction to Computer Vision Module 2: Machine Learning on AWS AWS Machine Learning Stack Data in Machine Learning...