What Qualifications Do I Need for Machine Learning?

 What Qualifications Do I Need for Machine Learning?

Machines have made our life much much easier. Technological advancements in Artificial Intelligence and Machine Learning have made people rely on them for almost all of their tasks.

“Machine Learning saves costs and eliminates a lot of work that humans find unpleasant while allowing us to focus on the more strategic and people-centric aspects of our jobs.”

  • Jack McCullough, President, the CFO Leadership Council

This is the reason that companies are emphasizing more machine learning approaches for tasks such that they can shift their focus to more important tasks to improve their productivity and in turn ROIs.

While AI tries to mimic human behavior, it is machine learning that works behind the scenes and trains machines to recognize and learn patterns from data. The machine is trained such that it can perform tasks without or at least human intervention.

The capabilities in machine learning are widely looked for, and if you are willing to step into the world of Machine Learning, the right time is NOW.

Let’s now read in brief about machine learning and the requirements for learning this technology.

What is Machine Learning?

The technique that enables you to create machines capable of analyzing the data, learning and identifying patterns, and making predictions/decisions with minimal or no human interference, is referred to as Machine Learning.

Simply put, Machine Learning is a methodology used to train a computer to learn from existing data to perform the specified tasks with no errors.

The point to be noted here is that machine learning is taught with data; it is not programmed.

It is machine learning that gives you a more personalized, innovative experience on social media platforms; it is ML that is used in the healthcare sector to keep patients updated and also in the diagnosis of diseases at early stages; it is ML that gives you suggestions on Netflix (or any other OTT platform) for the movies that you might wish to watch.

It can be observed that ML finds its applications in almost all the industries, across all sectors. It is the most important component of Artificial Intelligence.

Prerequisites for learning Machine Learning

Professionals taking Machine Learning courses in Hyderabad are not required to fulfill requirements, besides having a bachelor’s degree in computer science, or equivalent qualification. It is all about working with programming languages, linear equations, statistics, histograms, variables, etc.

If you have decided to make a career in machine learning and wish to know what you are required to be well-versed in, here goes the list!

  1. Statistics

Statistics involves collecting the data, sorting, analyzing, interpreting, and presenting the data.  Statistics, as we have studied in our high school years, is about observing the given data, sorting or arranging it, and then making a chart of graphs to represent it in a user-readable format.

When statistics is related to machine learning, it comes in two types: descriptive statistics and inferential statistics. Descriptive statistics deals usually with numbers to describe the specified data set. It strives to describe the given data set in a meaningful format. On the other hand, inferential statistics enables you to extract conclusions from a sample in place of the complete data set.

The terminology in statistics that you are required to master is Standard deviation, mean, mode, Histogram, Outliers, Pie charts, Ogive, etc.

  1. Linear Algebra

An integral part of machine learning is Linear Algebra. Linear algebra in machine learning covers the fundamental concepts of matrices, vectors, and linear transformation.

Some of the concepts of linear algebra that you are required to know in-depth are notations, multiplication of matrices, tensor, and tensor rank, algorithms in code, etc.

  1. Programming Languages

Working in machine learning requires you to have a sound knowledge of popular programming languages including R, Python, C#, Java, etc.

Knowledge of programming languages enables you to understand the internal mechanisms of systems that are fed with machine learning algorithms.

Some of the most popular programming languages and their features are mentioned below.

  1. Python

Some of the special features of Python include its easy syntaxes, huge support for packages, built-in functions that enable beginners to use this language easily. It has the most number of supported libraries. It allows you to access more than 235,000 packages through Python Package Index (PyPI). It has huge community support as well.

Some of the popular libraries in Python are NumPy(meant for mathematical operations), PyTorch and TensorFlow (meant for Deep Learning), Scikit-learn (for regression and classification algorithms), Matplotlib (for data visualization), OpenCV, and Dlib (for file operations).

  1. R

When you look for prerequisites for a profession in machine learning, you will find R as one of the top priority languages. R enables you to implement different machine learning applications. R has great support for libraries.

Some of the packages that R supports widely are DataExplorer for data exploration, SuperML and Rpart for machine learning, Mlr3 meant for managing machine learning workflows, ggplot and Plotly meant for data visualization, Caret and Kernlab for classification and regression-based operations, and many more.

Other popular languages you can master are MATLAB and C++ and more.

  1. Calculus

You need a strong understanding of calculus to build machine learning models. For various machine learning algorithms, calculus forms an integral part. For gaining expertise in calculus, you should learn partial derivatives, slope or gradient, integration and differentiation, chain rules meant for training neural networks.

  1. Probability

Machine learning models mostly work on the concepts of probability (as in the recommendation engine). Almost all data-driven decisions are made on the basis of probability.

Some of the concepts of probability that you need to learn are continuous random variables, independence, probability distribution, conditional and joints, sum rule, Bayes theorem, and chain or product rule.

Conclusion

You have now come across the prerequisites for machine learning. To become an expert in machine learning and learn the required technologies, here is the one-stop solution.

An online training course from an accredited institute.

Hyderabad, a city that serves great professionals for technologies like Artificial Intelligence and Machine Learning, is one of the best locations where your skills gained through an online training course can be utilized.

Enroll Now!!

Shabbir Ahmad

https://shiftedmag.com

Shabbir Ahmed is a Professional Blogger, Writer, SEO Expert & Founder of Dive in SEO. With over 5 years of experience, he handles clients globally & also educates others with different digital marketing tactics.

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