How to start a career in Deep Learning Engineering?

Data Science, AI and ML
#1

Deep learning provides attractive employment options for programmers and computer scientists that are interested. However, there are some things that one should be aware of before embarking on a deep learning career path. We’ve put up a list of advice for pursuing a successful deep learning career.

One of the most promising advancements in artificial intelligence research is deep learning. Deep learning is a portion of machine learning algorithms that examine data sets in real-time to enhance performance. It uses unstructured data to create artificial neural networks that categorize and evolve from the data they process.

To start deep learning follow the below given simple steps:

  1. Know the Pre-requisites
    Before diving into Deep Learning, it’s a good idea to brush up on the fundamentals of machine learning. The Machine Learning Learning Path is a comprehensive guide to getting started in the area.
    In short, learn:
  • Math Fundamentals
  • Python Fundamentals
  • Statistics Fundamentals
  • Machine Learning Fundamentals

  1. Setup your Machine
    Make sure you have the required hardware before moving on to the next stage. At the very least, it is advised that you have at least
    A GPU with 4+ GB, preferably Nvidia
    CPU with Intel i3
    4 GB RAM or more

  2. Understand better
    Now that you have a basic understanding of the prerequisites, you should go on to learn more about Deep Learning.

  3. The Deep Dive
    You’re almost ready to etch your name into the Deep Learning Hall of Fame! The road ahead is long and winding (pun intended) and mainly uncharted territory. It is now up to you to use your newly learned expertise to the best possible use.