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Why Do Some Machine Learning Models Fail?

Big Data LDN 2019 | Why Do Some Machine Learning Models Fail? | Rafael Garcia-Dias

Most Machine Learning (ML) talks present beautiful cases of success, but, in reality, ML models often fail to deliver the desired performance. It is not uncommon to see developers blaming certain ML models and even providing blacklists of ML models. In this talk, Rafael Garcia-Dias will provide some tips on choosing ML models and guide them through the path of finding a good solution. Rafael will also present two of his recent works that use machine learning in astrophysics and in neuroscience.

This course is no longer available. Find a similar course by searching these:

machine learning models model failure analysis machine learning performance tuning big data ldn neuroscience astrophysics

What's inside

Syllabus

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Teaches remedies for when Machine Learning (ML) models fail, which is extremely common

Instructs on how to choose optimal ML models based on the problem statement

Features real-world examples from astrophysics and neuroscience of ML implementation

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Learners who complete Why Do Some Machine Learning Models Fail? will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist uses advanced statistical analysis and machine learning to extract insights from data in order to improve business decision-making. This course may be useful for a Data Scientist to gain a better understanding of why some machine learning models fail and how to use this knowledge to build more effective models.

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Software Engineer

A Software Engineer designs, develops, and maintains software systems. This course may be useful for a Software Engineer to gain a better understanding of the challenges of machine learning and how to build more robust and reliable software systems.

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Database Administrator

A Database Administrator manages and maintains databases. This course may be helpful for a Database Administrator to gain a better understanding of how machine learning can be used to improve database performance and security.

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Business Analyst

A Business Analyst helps businesses understand their data and make better decisions. This course may be useful for a Business Analyst to gain a better understanding of how machine learning can be used to improve business intelligence and analytics.

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Data Analyst

A Data Analyst collects, analyzes, and interprets data to help businesses make better decisions. This course may be useful for a Data Analyst to gain a better understanding of how machine learning can be used to improve data analysis and decision-making.

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Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be useful for a Machine Learning Engineer to gain a better understanding of why some machine learning models fail and how to build more effective models.

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Statistician

A Statistician uses statistical methods to collect, analyze, and interpret data. This course may be useful for a Statistician to gain a better understanding of how machine learning can be used to improve statistical analysis and modeling.

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Research Scientist

A Research Scientist conducts research to develop new knowledge and technologies. This course may be useful for a Research Scientist to gain a better understanding of how machine learning can be used to improve research methods and outcomes.

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Data Engineer

A Data Engineer designs, builds, and maintains data pipelines. This course may be helpful for a Data Engineer to gain a better understanding of how machine learning can be used to improve data quality and efficiency.

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Product Manager

A Product Manager manages the development and launch of new products. This course may be useful for a Product Manager to gain a better understanding of how machine learning can be used to improve product design and development.

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Project Manager

A Project Manager plans and manages projects to ensure their successful completion. This course may be helpful for a Project Manager to gain a better understanding of how machine learning can be used to improve project planning and management.

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Technical Writer

A Technical Writer creates and maintains technical documentation. This course may be helpful for a Technical Writer to gain a better understanding of how machine learning can be used to improve the quality and effectiveness of technical documentation.

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Business Intelligence Analyst

A Business Intelligence Analyst helps businesses understand their data and make better decisions. This course may be useful for a Business Intelligence Analyst to gain a better understanding of how machine learning can be used to improve business intelligence and analytics.

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Data Architect

A Data Architect designs and manages data architectures. This course may be helpful for a Data Architect to gain a better understanding of how machine learning can be used to improve data architecture and management.

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Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical methods to analyze financial data. This course may be useful for a Quantitative Analyst to gain a better understanding of how machine learning can be used to improve financial analysis and modeling.

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