What is Tensorflow | Why to use Tensorflow | Business Usecases
Coding skills: Building ML models involves much more than just knowing ML concepts—it requires coding in order to do the data management, parameter tuning, and parsing results needed to test and optimize your model.
Math and stats: ML is a math heavy discipline, so if you plan to modify ML models or build new ones from scratch, familiarity with the underlying math concepts is crucial to the process.
ML theory: Knowing the basics of ML theory will give you a foundation to build on, and help you troubleshoot when something goes wrong.
Build your own projects: Getting hands on experience with ML is the best way to put your knowledge to the test, so don’t be afraid to dive in early with a simple colab or tutorial to get some practice.