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Why The Best Data Scientists have Mastered Algebra, Calculus and Probability
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All the outstanding data scientist and ML engineers have one thing in common:
They have a strong, working understanding of how ML's high-level software libraries work. Being able to look under the hood, and understand what's going in libraries such as scikit-learn, TensorFlow, and Keras, is what makes a data scientist and ML engineer exceptional.
Throughout this webinar, you'll walk through the four core subjects that serve as the building blocks for understanding how ML algorithms work:
Linear Algebra
Calculus
Probability Theory
Computer Science
In each part, you'll learn not only what the subject is about, but also why it's relevant to ML and even a hands-on code demo in Python!
They have a strong, working understanding of how ML's high-level software libraries work. Being able to look under the hood, and understand what's going in libraries such as scikit-learn, TensorFlow, and Keras, is what makes a data scientist and ML engineer exceptional.
Throughout this webinar, you'll walk through the four core subjects that serve as the building blocks for understanding how ML algorithms work:
Linear Algebra
Calculus
Probability Theory
Computer Science
In each part, you'll learn not only what the subject is about, but also why it's relevant to ML and even a hands-on code demo in Python!