Search result for Data analysis and machine learning Online Courses & Certifications
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Supervised Machine Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.7
Approx. 11 hours to complete
This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Regression techniques in a business setting. Introduction to Supervised Machine Learning and Linear Regression Introduction to Supervised Machine Learning: What is Machine Learning? Introduction to Supervised Machine Learning: Types of Machine Learning Supervised Machine Learning for Interpretation and Prediction Data Splits and Cross Validation...
Production Machine Learning Systems
by Google Cloud Training- 4.6
Approx. 8 hours to complete
In the second course of this specialization, we will dive into the components and best practices of a high-performing ML system in production environments. The Components of an ML System: Data Analysis and Validation Ingesting data for Cloud-based analytics and ML Ingesting data for Cloud-based analytics and ML Machine Learning on Hybrid Cloud...
Foundations: Data, Data, Everywhere
by Google Career CertificatesTop Instructor- 4.8
Approx. 20 hours to complete
- Discover a wide variety of terms and concepts relevant to the role of a junior data analyst, such as the data life cycle and the data analysis process. Learning about data phases and tools The data analysis process and this program Learning Log: Reflect on the data analysis process Data analyst roles and job descriptions...
Introduction to Machine Learning Course
by Katie Malone , Sebastian Thrun- 0.0
Timeline Approx. 10 Weeks
This class will teach you the end-to-end process of investigating data through a machine learning lens. lesson 5 Choose your own Algorithm Decide how to pick the right Machine Learning Algorithm among K-Means, Adaboost, and Decision Trees. lesson 6 Datasets and Questions Apply your Machine Learning knowledge by looking for patterns in the Enron Email Dataset....
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Machine Learning: Classification
by Emily Fox , Carlos Guestrin- 4.7
Approx. 21 hours to complete
You will implement these technique on real-world, large-scale machine learning tasks. You will also address significant tasks you will face in real-world applications of ML, including handling missing data and measuring precision and recall to evaluate a classifier. Task of learning decision trees from data Timeline of scalable machine learning & stochastic gradient...
Introduction to Machine Learning
by Lawrence Carin , David Carlson , Timothy Dunn , Kevin Liang- 4.7
Approx. 26 hours to complete
This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc. Simple Introduction to Machine Learning Deep Learning and Transfer Learning Intro to Machine Learning Transfer Learning and Fine-Tuning Limitations of Q Learning, and Introduction to Deep Q Learning...
Innovations in Investment Technology: Artificial Intelligence
by Andrew Wu , Robert Dittmar- 4.7
Approx. 11 hours to complete
Explore the evolution of AI investing and online wealth management. Moving from human-based data-driven investing strategies to neural networks, you’ll assess the ability of artificial intelligence to make investment decisions and discover the role of AI and machine learning in making trading decisions. Fintech Innovations: Series Map and Learning Goals Stock Selection Screening: Discovering Signals and Data Issues...
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Probabilistic Graphical Models 3: Learning
by Daphne Koller- 4.6
Approx. 66 hours to complete
These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are also a foundational tool in formulating many machine learning problems. Review of Machine Learning Concepts from Prof. Andrew Ng's Machine Learning Class (Optional) Learning General Graphs: Search and Decomposability...
Machine Learning for Data Analysis
by Jen Rose , Lisa Dierker- 4.2
Approx. 10 hours to complete
This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering....
Big Data Emerging Technologies
by Jong-Moon Chung- 4.7
Approx. 30 hours to complete
Then the lectures focused on how big data analysis is possible based on the world’s most popular three big data technologies Hadoop, Spark, and Storm. The last part focuses on providing experience on one of the most famous and widely used big data statistical analysis systems in the world, the IBM SPSS Statistics....