Search result for Introduction to genetic algorithm Online Courses & Certifications
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Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
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Approx. 9 hours to complete
You will learn several clustering and dimension reduction algorithms for unsupervised learning as well as how to select the algorithm that best suits your data. Introduction to Unsupervised Learning and K Means Introduction to Unsupervised Learning - Part 1 Introduction to Unsupervised Learning - Part 2 Introduction to Clustering Introduction to Unsupervised Learning...
Blockchain Scalability and its Foundations in Distributed Systems
by Vincent Gramoli- 4.7
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Approx. 11 hours to complete
Blockchain promises to disrupt industries once it will be efficient at large scale. In this course, you will learn how to make blockchain scale. Introduction to the course Introduction to Module 1 How to navigate the MOOC Introduction to Module 2 Introduction to Module 3 Introduction to Module 4 Introduction to Module 5...
Forex Robots: Automate Your Trading - Practice EA Included!
by Kirill Eremenko- 4.7
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5.5 hours on-demand video
Forex Robots - Learn the secrets to trading Forex in MetaTrader 4 with Automated Forex Trading Systems Learn how to Test & Optimize Forex Robots in MetaTrader 4. Apply a tried & tested Stability Criteria to FX Robots Take advantage of the Genetic Algorithm and 2D-surface in MT4 Take advantage of the Genetic Algorithm and 2D-surface in MT4...
$20.99
Geometric Algorithms
by Kevin Buchin- 0.0
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Approx. 18 hours to complete
Course Information: In many areas of computer science such as robotics, computer graphics, virtual reality, and geographic information systems, it is necessary to store, analyze, and create or manipulate spatial data. - to decide which algorithm or data structure to use in order to solve a given basic geometric problem, Introduction to Range Searching...
Bayesian Methods for Machine Learning
by Daniil Polykovskiy , Alexander Novikov- 4.5
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Approx. 33 hours to complete
People apply Bayesian methods in many areas: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Introduction to Bayesian methods & Conjugate priors Bayesian approach to statistics How to define a model Introduction to Bayesian methods...
Build Regression, Classification, and Clustering Models
by Anastas Stoyanovsky- 0.0
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Approx. 20 hours to complete
In most cases, the ultimate goal of a machine learning project is to produce a model. You need to know how to select the best algorithm for a given job, and how to use that algorithm to produce a working model that provides value to the business. Build Linear Regression Models Using Linear Algebra Module Introduction...
人工智慧：機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)
by 于天立- 4.6
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Approx. 12 hours to complete
1-1 Brief Introduction to Machine Learning, Learning from Example 1-3 The Find-S Algorithm 1-4 Version Space and The List-Then Eliminate Algorithm 1-5 The Candidate Elimination Algorithm 2-1 Introduction to Computational Learning Theory, Setting of Sample Complexity 2-8 The Weighted-Majority Algorithm and its Bound 4-1 Introduction to Neural Network...
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Data Science Fundamentals for Data Analysts
by Emma Freeman , Mark Roepke- 0.0
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Approx. 19 hours to complete
First, we’ll give you a quick introduction to data science - what it is and how it is used to solve real-world problems. Introduction to Delta Lake An Introduction to Data Science An Introduction to Statistics An Introduction to Probability An Introduction to Probability Distributions An Introduction to Hypothesis Testing Introduction to Machine Learning, Part 1...
Graph Theory Algorithms
by William Fiset- 4.6
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9 hours on-demand video
This course provides a complete introduction to Graph Theory algorithms in computer science. Dijkstra's algorithm Topological sort algorithm Bellman Ford's algorithm Floyd-Warshall all pairs shortest path algorithm How to find the maximum flow of a flow graph Various network flow algorithms including: Edmonds-Karp, Capacity Scaling, and Dinic's algorithm Kruskal's Minimum Spanning Tree algorithm...
$21.99
Bioinformatics Capstone: Big Data in Biology
by Phillip Compeau , Pavel Pevzner- 4.1
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Approx. 14 hours to complete
In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. Plus, hacker track students will have the option to build their own genome assembler and apply it to real data! Introduction Introduction...
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