Learn About Machine Learning Before Pursuing a Career!

Machine learning is a subset of Artificial intelligence that deals with machines’ ability to learn on their own without an individual’s help. Thanks to the constant hard work by machine learning developers, computers can identify trends, patterns, and errors in data quicker and more efficiently. This field has a huge impact on all our lives as we experience it on a daily basis, but still, people are confused about what ML is and where it is used.

How is ML used?

This field can be used to predict an outcome in a particular situation or to replicate specific human actions. The tasks are carried out using various algorithms such as SVM, logistic regression, linear regression, and Naïve Bayes classifiers, etc.

ML can be divided into three categories:

• Supervised learning: In this form of ML, the data is fed to a computer with a specific outcome in mind. For example, machines can be taught to calculate the weight of coins and differentiate them based on that. This way, the device will be able to figure out the type of coins according to their weight. It is known as the labeled data.
• Unsupervised learning: This type does not use any labeled data which means the machines would independently analyze patterns and identify trends in a given dataset.
• Reinforcement learning: It is a guided form of learning where the machines are told when they are making a mistake and then set-up to correct them as well.

ML Salaries and Job Prospects

Once you complete machine learning training, you will be eligible for a range of jobs in the industry but the most common one is a machine learning engineer. Luckily, ML engineers are in high demand these days and earn really good salaries. That is mainly because the total number of ML professionals is very less in the industry. An average, ML engineer can earn around $112,350 per year so if you want to pursue a career in this field, you either need a bachelor’s degree or pass a coding boot camp. Other than this, you can choose to become a data scientist, ML research scientist, or senior ML engineer.

Required skills and duties involved

Skills

Just like any other software developer, you need to have a basic understanding of computer science basics like computer architecture, data structure, and programming. ML is heavily based on probability and statistics, so you need to have a good knowledge of these two concepts as well. Data modeling skills are also essential in ML as they help define and analyze the data set to come up with valuable insights.

Job duties

The first task includes developing ML applications to meet project requirements. To carry this out successfully, you will need to perform data collection, problem framing, and feature engineering. ML also requires you to perform experiments using various methods. Choosing appropriate data analyzing models is also an important step in the ML engineer’s job profile.

Benefits of becoming an ML Engineer

ML is a field that allows you to solve real-world problems and devise practical solutions. Once you finish the machine learning bootcamp, you will have access to plenty of job opportunities that pay really well too. By working on ML algorithms, you will develop superior analytical and creative skills along with getting a chance to work on futuristic technology.

Advance your career by beginning your training

If you want to become an expert in this domain, you need to get professional training. ML bootcamps allow you to become an engineer within a span of 4-5 months. SynergisticIT is one of the best camps in the Bay area that covers everything from data science, artificial intelligence, deep learning, and Computer science along with other needed frameworks and libraries. Their training covers both theoretical and practical aspects of the curriculum to fast track your career. So get the apt industry exposure by signing up at the right place!

Also, Read This Blog: Begin your data science journey the right way!