Search result for Introduction to machine learning Online Courses & Certifications
Get Course Alerts by Email
Google Cloud Big Data and Machine Learning Fundamentals
by Google Cloud Training- 4.7
Approx. 12 hours to complete
Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. Introduction to the Data and Machine Learning on Google Cloud Course Welcome to Big Data and Machine Learning Fundamentals Introduction to machine learning...
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center
by Avi Ma’ayan, PhD- 4.8
Approx. 9 hours to complete
Introduction to LINCS L1000 Data Introduction to Metadata and Ontologies | Part 1 Introduction to Metadata and Ontologies | Part 2 Data Clustering | Part 1 | Introduction Machine Learning Introduction to Machine Learning | Part 1 Introduction to Machine Learning | Part 2 Introduction to Machine Learning | Part 3...
Applied Data Science for Data Analysts
by Kevin Coyle , Mark Roepke , Emma Freeman- 4.2
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. Machine Learning Workflow Introduction to Databricks (Optional) Introduction to the Platform (Optional) Introduction to Apache Spark (Optional) Introduction to Hyperparameters Introduction to Cross-Validation...
Intro to Self-Driving Cars
by Sebastian Thrun , Andy Brown , Cezanne Camacho , Andrew Paster , Anthony Navarro , Elecia White , Tarin Ziyaee- 0.0
4 Months
Self-driving cars are the future of smart transportation, and this introductory program is the perfect way to start your journey to a self-driving car career! This program enables anyone with minimal programming experience to learn the essentials of programming a self-driving car, from machine learning to object-oriented programming to probabilistic robotics....
The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
by Eric Siegel- 4.8
Approx. 14 hours to complete
In order to serve both types, this course goes further than typical machine learning courses, which cover only the technical foundations and core quantitative techniques. – What your data needs to look like before applying machine learning The contents and learning objectives apply, regardless of which machine learning software tools you end up choosing to work with....
Applied AI with DeepLearning
by Romeo Kienzler , Niketan Pansare , Tom Hanlon , Max Pumperla , Ilja Rasin- 4.4
Approx. 24 hours to complete
This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. Introduction to deep learning...
Machine Learning Algorithms: Supervised Learning Tip to Tail
by Anna Koop- 4.7
Approx. 9 hours to complete
This course takes you from understanding the fundamentals of a machine learning project. To be successful, you should have at least beginner-level background in Python programming (e. This is the second course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute. Introduction to the Course...
Eigenvectors and Eigenvalues
by Ortal Arel- 0.0
Approx. 1 weeks
In the computational world of AI you will often encounter enormous amounts of data that needs to be processed. Learn how to calculate eigenvalues and eigenvectors and why they are important for AI applications. lesson 1 Vectors Linear Transformation lesson 2 Definitions and Calculations Characteristic Equation of a matrix Eigenvalues Eigenvectors lesson 3 Why is the relevant to Machine Learning?...
Free
Deep Learning and Reinforcement Learning
by Mark J Grover , Miguel Maldonado- 4.7
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....
Using Machine Learning in Trading and Finance
by Jack Farmer , Ram Seshadri- 4
Approx. 19 hours to complete
By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. Welcome to Using Machine Learning in Trading and Finance...