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Applied Machine Learning in Python
by Kevyn Collins-Thompson- 4.6
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Approx. 34 hours to complete
This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. Key Concepts in Machine Learning...
Python and Machine Learning for Asset Management
by John Mulvey - Princeton University , Lionel Martellini, PhD- 3
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Approx. 17 hours to complete
Supervised learning Unsupervised learning Machine Learning for Investment Decisions: A Brief Guided Tour Machine learning techniques for robust estimation of factor models Penalty methods References for module 2"Machine learning techniques for robust estimation of factor models" Machine learning techniques for efficient portfolio diversification Introduction to module 3 -Machine learning techniques for efficient portfolio diversification Several Machine Learning Methods...
Introduction to Machine Learning
by Lawrence Carin , David Carlson , Timothy Dunn , Kevin Liang- 4.7
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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. Methods for Learning Model Parameters Limitations of Q Learning, and Introduction to Deep Q Learning Deep Q Learning Based on Images Connecting Deep Q Learning with Conventional Q Learning...
Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls
by Eric Siegel- 4.8
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Approx. 17 hours to complete
This course will show you how machine learning works. MODULE 2 - Standard, Go-To Machine Learning Methods DEMO - Autotuning a machine learning model (optional) Compare and contrast: summary of ML methods Machine learning software: dos and don'ts for choosing a tool Machine learning software: how tools vary and how to choose one...
AI Workflow: Machine Learning, Visual Recognition and NLP
by Mark J Grover , Ray Lopez, Ph.D.- 4.5
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Approx. 14 hours to complete
Explain the use of linear and logistic regression in supervised learning applications Explain the use of tree-based algorithms in supervised learning applications Explain the use of Neural Networks in supervised learning applications This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises....
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
by Andrew NgTop Instructor , Kian KatanforooshTop Instructor , Younes Bensouda MourriTop Instructor- 4.9
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Approx. 22 hours to complete
In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. Practical Aspects of Deep Learning Other Regularization Methods Practical aspects of Deep Learning Learning Rate Decay Clarification about Learning Rate Decay Video...
Guitar Simplified - Master the chords, beats & rhythms
by Yeeshu Sharma- 4.6
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8 hours on-demand video
Beginners guide to learning guitar step-by-step using theory and practical methods. I have devoted 11 years to guitar learning and have taught a lot of students over the past 8 years. let's make guitar learning fun !!!!! But , before that , let me answer your most asked questions about....
$12.99
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Machine Learning Technical Interview
by Vladimir Poliakov- 3.6
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5 hours on-demand video
Get ready for a technical Machine Learning interview / Data Science interview by mastering commonly asked questions! In summary, this course will help you to recall the methods used by real machine learning experts and prepare you for this hot data scientist career path. Understand the pros and cons between machine learning methods...
$11.99
Overview of Advanced Methods of Reinforcement Learning in Finance
by Igor Halperin- 3.8
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Approx. 13 hours to complete
In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. - Apply the methods of Reinforcement Learning to high-frequency trading, credit risk peer-to-peer lending, and cryptocurrencies trading. Reinforcement Learning and Ptolemy's Epicycles...
Ensemble Machine Learning in Python: Random Forest, AdaBoost
by Lazy Programmer Team- 4.6
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5.5 hours on-demand video
Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. We've already learned some classic machine learning models like k-nearest neighbor and decision tree. Simple machine learning models like linear regression and decision trees...
$29.99
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