Description
To be an honest data scientist, you would like to understand the way to use data science and machine learning libraries and algorithms, like NumPy, TensorFlow and PyTorch, to unravel whichever problem you’ve got at hand.
To be a superb data scientist, you would like to understand how those libraries and algorithms work.
This is where our course “Machine Learning & Data Science Foundations Masterclass” comes in. Led by deep learning guru Dr. Jon Krohn, this first entry within the Machine Learning Foundations series will offer you the fundamentals of the mathematics like algebra , matrices and tensor manipulation, that operate behind the foremost important Python libraries and machine learning and data science algorithms.
The first step in your journey into becoming a superb data scientist is weakened as follows:
Section 1: algebra Data Structures
Section 2: Tensor Operations
Section 3: Matrix Properties
Section 4: Eigenvectors and Eigenvalues
Section 5: Matrix Operations for Machine Learning
Throughout each of the sections, you will find many hands-on assignments and practical exercises to urge your math game up to speed!
Are you able to become a superb data scientist? Enroll now!
See you within the classroom.
Who this course is for:
You use high-level software libraries (e.g., scikit-learn, Keras, TensorFlow) to coach or deploy machine learning algorithms, and would now wish to understand the basics underlying the abstractions, enabling you to expand your capabilities
You’re a software developer who would really like to develop a firm foundation for the deployment of machine learning algorithms into production systems
You’re a knowledge scientist who would really like to strengthen your understanding of the themes at the core of your professional discipline
You’re a knowledge analyst or A.I. enthusiast who would really like to become a knowledge scientist or data/ML engineer, then you’re keen to deeply understand the sector you’re entering from the bottom up (very wise of you!)
