How much python is required for Machine Learning Quora?

Basically, Python is a very easy language and if you know little bit of concepts about coding then you can easily learn python. Otherwise i will suggest that you should start reading about the python basics and don’t give more than three days to it.

Are ML engineers in demand?

As machine learning makes huge inroads into various industries, the demand for machine learning engineers is also on the rise. The time is ripe to make a career in the ML/AI field. The AI specialist role has seen a 74\% annual growth rate in the past four years.

What to expect in machine learning engineering for production specialization?

In the fourth course of Machine Learning Engineering for Production Specialization, you will learn how to deploy ML models and make them available to end-users. You will build scalable and reliable hardware infrastructure to deliver inference requests both in real-time and batch depending on the use case.

What are the challenges of machine learning?

The challenge of an ML process is to create a bridge between these two planes in a controlled way. Code and data evolve independently. We can think of them as separate planes with a common time dimension.

What does it take to build a successful machine learning application?

Establish a model baseline, address concept drift, and prototype how to develop, deploy, and continuously improve a productionized ML application. Build data pipelines by gathering, cleaning, and validating datasets.

What is machine learning at Stanford University?

Machine Learning (Stanford University, +3M students). This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).