Search result for Probabilistic algorithms Online Courses & Certifications
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Probabilistic Graphical Models 2: Inference
by Daphne Koller- 4.6
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Approx. 38 hours to complete
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. Following the first course, which focused on representation, this course addresses the question of probabilistic inference: how a PGM can be used to answer questions. Belief Propagation Algorithms MAP Algorithms...
Machine Learning
by John W. Paisley- 0.0
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12 Weeks
Master the essentials of machine learning and algorithms to help improve learning from data without human intervention. probabilistic versus non-probabilistic modeling We will discuss several fundamental methods for performing this task and algorithms for their optimization. Probabilistic versus non-probabilistic viewpoints Optimization and inference algorithms for model learning...
$249
Autonomous Mobile Robots
by Roland Siegwart , Margarita Chli , Marco Hutter , Davide Scaramuzza- 0.0
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15 Weeks
Basic concepts and algorithms for locomotion, perception, and intelligent navigation. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. Be able to describe the basic concepts and algorithms required for mobile robot locomotion, environment perception, probabilistic map based localization and mapping, and motion planning...
$50
Quantum Machine Learning
by Peter Wittek- 0.0
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9 Weeks
In this course we will introduce several quantum machine learning algorithms and implement them in Python. Sample quantum states for probabilistic models. ·      Implement learning algorithms on quantum computers in Python...
$49
Probabilistic Graphical Models 3: Learning
by Daphne Koller- 4.6
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Approx. 66 hours to complete
Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. The (highly recommended) honors track contains two hands-on programming assignments, in which key routines of two commonly used learning algorithms are implemented and applied to a real-world problem....
Machine Learning with Python: from Linear Models to Deep Learning
by Regina Barzilay , Tommi Jaakkola , Karene Chu- 0.0
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15 Weeks
, Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk. Clustering, classification, recommender problems, probabilistic modeling, reinforcement learning; Students will implement and experiment with the algorithms in several Python projects designed for different practical applications....
$300
Learn Algorithms and Data Structures in Java
by Packt Publishing- 3.6
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2.5 hours on-demand video
Leverage Java Algorithms for Operational Efficiency Programs are created from algorithms and data structures. You’ll get familiar with multithreading algorithms and probabilistic algorithms. It will help you to gain in-demand knowledge of key data structures and algorithms and prepare you for the next stage in your career as a developer....
$9.99
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Computational Thinking and Big Data
by Lewis Mitchell , Markus Wagner , Simon Tuke , Gavin Meredith- 0.0
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10 Weeks
You will develop skills in data-driven problem design and algorithms for big data. The course will also explain mathematical representations, probabilistic and statistical models, dimension reduction and Bayesian models....
$249
Computational Probability and Inference
by George H. Chen , Polina Golland , Gregory W. Wornell , Lizhong Zheng- 0.0
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12 Weeks
Learn fundamentals of probabilistic analysis and inference. You will learn about different data structures for storing probability distributions, such as probabilistic graphical models, and build efficient algorithms for reasoning with these data structures. Algorithms for prediction and inference How to model real-world problems in terms of probabilistic inference...
$49
Bayesian Methods for Machine Learning
by Daniil Polykovskiy , Alexander Novikov- 4.5
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Approx. 33 hours to complete
In six weeks we will discuss the basics of Bayesian methods: from how to define a probabilistic model to how to make predictions from it. Probabilistic clustering K-means from probabilistic perspective Probabilistic PCA EM for Probabilistic PCA...
