5 Must Have Machine Learning Skills

Amazon, Google, and Microsoft offer Machine Learning as a service for businesses to derive more meaning from their data. Therefore, individuals can apply the algorithms behind their complex systems to build more powerful applications.

Furthermore, Microsoft offers Cortana Analytics, a fully managed big data management and advanced analytics suite that enables you to transform your data into intelligent action. In addition, it includes powerful machine learning and Hadoop-based advanced analytics for driving action in real time. It is intended to help organisations predict outcomes and prescribe decisions.

As machine learning capabilities take centre stage in most transformation projects. We look at the top 5 most sought-after Machine Learning skills in candidates.

5 Skills

1. Programming and Computer Science Principles
   Knowing the basics like data structures, algorithms and computer architecture is important. The ability to implement, apply and adapt them while programming. Coding exercises, competitions or hackathons are great ways to improve your skills in this.
2. Statistics and Probability
   Understanding the different probability theories underpin Machine Learning algorithms and the fundamentals of probability. Knowledge of statistics is also crucial to build and validating models from data.
3. Modelling and Evaluating Data
   The skill to approximate the structure of a dataset and the ability to see patterns or predict the properties of occurrences that haven’t come up before. It’s also vital to continuously evaluate the model being used to choose a useful appropriate accuracy/error measure that allows you to continually tweak your model.
4. Algorithms and Libraries
   Implementing Machine Learning algorithms involves the selection of an appropriate model, the right libraries and packages, a procedure to fit the data and understanding how these parameters will affect learning. It’s also important to know the pros and cons of each approach and then the potential pitfalls of using a certain model over another.
5. Software Engineering and System Design
   A software design engineer (SDE) is a key member of a software development company. He or she helps identify problems and figures out how to create programs that will automate or ease those situations. Understanding how all the pieces work together when developing the ecosystem that fits into a product or service. A Machine Learning Engineer’s goal is to deliver a piece of software. Understanding the potential pitfalls caused by not being able to scale your algorithms is important for productivity, quality and collaboration.