In this machine learning course by google you have not required any prior knowledge of machine learning.
You need some Basic mathematical algebra concepts, Tensor flow basics and some basic knowledge of Python programming which is I describe below which help you learning better about machine learning.
I am sure this course will help you learning about machine learning fundamental which increase your interest in machine learning.
What is tensor flow?
Tensor flow is open source library for data flow programming across a range of tasks. It is symbolic math library and is also used for machine learning application such as neural networks.
It is used by google and released under Apache 2.0 open source license.
for knowing about it or use it you can visit its official site https://www.tensorflow.org/.
Key concept and tools for this crash course
- Variable , coefficients and functions.
- Linear Equation
- Sigmoid function
- Tensor and Tensor rank
- Matrix Multiplication
- Mean, median and outliers.
- Ability to read a histogram.
- Concept of derivative .
- Gradient or slope.
- Partials derivatives.
- Chain rules (for understanding Backpropagation algorithm for training neural networks).
- Defining and calling function using positional and calling function.
- Dictionaries, list and sets.
- for loops.
- if/ else conditional blocks and expression.
- String formatting.
- variable assignment and basic data type.
- the pass statement.
Now some interesting topics which is discussed in course
- Descending into ML
- Reducing Loss
- First step with Tensor Flow
- Training and test sets
- Feature crosses
- Logistic regression
- Introduction to Neural nets
- Training Neural nets
for more information Visit: https://developers.google.com/machine-learning/crash-course/