Machine Learning: Random Forest with Python from Scratch - Past, Present, and Future of Machine Learning

Machine Learning: Random Forest with Python from Scratch - Past, Present, and Future of Machine Learning

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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The video discusses the evolution and boom of machine learning, highlighting the need for powerful machines and abundant data. It explores future applications like self-driving cars and gaming, and examines trends in AI publications and investments. The video concludes with an overview of the course structure.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

Why did machine learning not evolve significantly until around 2015?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the two main requirements for implementing machine learning algorithms practically?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

How does the computational power of quantum computers compare to that of supercomputers?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What role does data play in the performance of machine learning algorithms?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

In what ways are self-driving cars an example of machine learning applications?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

Discuss the significance of investments in AI startups since 2012.

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

What trends have been observed in AI job availability since 2013?

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