Search result for Model training and evaluation Online Courses & Certifications
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Machine Learning Foundations: A Case Study Approach
by Emily Fox , Carlos Guestrin- 4.6
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Approx. 18 hours to complete
Do you have data and wonder what it can tell you? Splitting the data into training and test sets Training and evaluating a classifier Document retrieval: A case study in clustering and measuring similarity Clustering and similarity ML block diagram Building & exploring a nearest neighbors model for Wikipedia articles Clustering and Similarity...
Managing Talent
by Scott DeRue, Ph.D. , Maxim Sytch, Ph.D. , Cheri Alexander- 4.6
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Approx. 12 hours to complete
In this course, you will learn best practices for selecting, recruiting, and onboarding talent. You will also learn about the key approaches to measuring performance and evaluating your employees. 02 - Strategy First and HR Planning Managing Performance Evaluation and Feedback Managing Performance Evaluation and Feedback 06 - Human Capital Systems and Succession Planning...
Artificial Intelligence Data Fairness and Bias
by Brent Summers- 4.9
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Approx. 6 hours to complete
In this course, we will explore fundamental issues of fairness and bias in machine learning. Fairness and protections in machine learning Model parity: a balancing act Building fair models: theory and practice Building an exploratory training set...
Investments I: Fundamentals of Performance Evaluation
by Scott Weisbenner- 4.7
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Approx. 27 hours to complete
We will study and use risk-return models such as the Capital Asset Pricing Model (CAPM) and multi-factor models to evaluate the performance of various securities and portfolios. • Use the Capital Asset Pricing Model (CAPM) and 3-Factor Model to evaluate the performance of an asset (like stocks) through regression analysis Market Anomalies: Small-Firm and Value Effects...
Business Model Innovation
by Laurence Lehmann-Ortega , Hélène Musikas- 4.7
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Approx. 14 hours to complete
Innovation goes beyond technology, products and processes. Over 150 companies that have successfully invented or reinvented their business model have been thoroughly analyzed and will inspire you to develop your own new, innovative business model. Define what a business model is and why it enables you to approach innovation and strategy from a completely different angle...
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
1-2 Hypotheses ,Relation between Instance Space and Hypotheses 1-4 Version Space and The List-Then Eliminate Algorithm 1-6 Biased and Unbiased Hypothesis Space, Futility of Bias-Free Learning 2-3 Exhausting the Version Space: Definition, Theorem ,Proof and some examples 2-5 Some examples and discussion about VC dimension 2-8 The Weighted-Majority Algorithm and its Bound...
Models & Frameworks to Support Sales Planning
by Nelson Yoshida , Edson Ito , Cesar Rodrigues , Samantha Mazzero- 4.4
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Approx. 22 hours to complete
Welcome to Course 3 - Models & Frameworks to Support Sales Planning – In this course, you’ll go through a conceptual approach to selling models and frameworks. As a primary learning outcome of this course, we emphasize the improvement in the analytical competencies and skills to develop sales planning and management....
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Fundamentals of Data Science with Python
by Packt Publishing- 3.8
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2.5 hours on-demand video
Implement powerful data science techniques with Python using NumPy, SciPy, Matplotlib, and scikit-learn He has spent the last 2 years teaching data science, emphasizing how to store, retrieve, and analyze data from any kind of database. Installing Python and Creating a First Jupyter Notebook Conditions and Loops Training a Model with Scikit-Learn...
$12.99
The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
by Eric Siegel- 4.8
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Approx. 14 hours to complete
Companies are seizing upon the power of this technology to combat risk, boost sales, cut costs, block fraud, streamline manufacturing, conquer spam, toughen crime fighting, and win elections. DEMO - Training a simple decision tree model (optional) Training data -- what it looks like DEMO - Training and comparing multiple models (optional)...
機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations
by 林軒田- 4.9
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Approx. 10 hours to complete
Our two sister courses teach the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. This first course of the two would focus more on mathematical tools, and the other course would focus more on algorithmic tools. Recap and Preview 第八講: Noise and Error...
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