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Learn Predictive Models, earn certificates with paid and free online courses from Yale, Columbia University, UC Davis, IIT Kharagpur and other top universities around the world. Read reviews to decide if a class is right for you.
Explore strategies for enhancing individualized predictive models in biomedical informatics, focusing on cutting-edge approaches and their potential impact on personalized healthcare.
Handle complex decisions with ease and confidence using powerful mathematical concept in this course taught by an award-winning mathematician.
Learn the linear algebra concepts behind machine learning.
Explore bias and discrimination in AI, covering types, fairness metrics, affected fields, and mitigation strategies. Learn from experts about ethical challenges in machine learning and algorithm design.
Learn how to apply advanced dimensionality techniques such as t-SNE and GLRM.
Transform big data prototypes into production-ready systems. Learn to measure performance, identify bottlenecks, and implement scalable solutions. Design load tests and optimize data stores for high-performance distributed systems.
Learn Fundamentals Of Data Science & Machine Learning With Rapidminer (No Coding). Dataset & Solutions Included.
Explore predictive modeling techniques to uncover complex data relationships, from linear and logistic regression to ANOVA, enhancing your ability to extract valuable insights for data-driven decision-making.
A hands-on approach to Machine Learning using the easy drag-n-drop environment of Azure Machine Learning Studio
Use the R Programming Language to execute data science projects and become a data scientist.
Machine Learning , Python, Advanced Data Visualization, R Programming, Linear Regression, Decision Trees, NumPy, Pandas
Explore the impact of proactive design on user experience, decision fatigue, and cultural shifts. Learn to create anticipatory software and distraction-free interfaces in this thought-provoking talk.
Explore DevOps principles for effective collaboration between data scientists and software engineers in machine learning projects, focusing on automated pipelines and best practices.
Explore deep learning models in genomics, uncovering latent biases and technical artifacts. Learn to design efficient models that correct biases and reveal novel insights into gene regulation.
Applying machine learning to JavaScript testing for efficient test selection, reducing unnecessary runs and improving overall testing effectiveness.
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