Your Ultimate Guide to Machine Learning

Machine learning or ML refers to the field of study that enables computers to make predictions and/or decisions based on what they have learned from the given data. Here, different types of advanced techniques are utilized to help a machine learning system (computer) perform. These days, machine learning has become extremely important. A lot of industries are now developing more powerful machine learning systems that can analyze more complex datasets and deliver more accurate results quickly. This enables businesses to identify strategic business opportunities, as well as, potential risks quickly. The availability of almost countless volumes of data and rapid advancements in the machine learning field has compelled industries, which depend on massive amounts of data, to embrace the technology to improve their bottom line.

 

Industries that greatly depend on machine learning

A lot of tech giants including IBM, Google, and Facebook have already started using machine learning as one of their primary technologies. Startups and small-scale businesses are also leaning toward using this technology to improve their functionalities and performances. Here’re some industries that are using machine learning to a great extent.

 

Transportation: None of us likes to sit in the vehicles and wait for the green lights, particularly when there is not any vehicle appearing from the other end. Thanks to machine learning, traffic lights have already started getting smart. In many countries, machine learning algorithms are efficiently monitoring and managing traffic. Most probably, you have already heard that self-driving cars are going to be the future of transportation. Once activated, the machine learning system in the vehicle can control its speed, park it, etc without requiring any input from the driver.

 

Finance: The finance sector has always been vulnerable to fraudulent activities. Financial institutions now, with the help of machine learning systems, can accurately identify signs of fraud and mitigate them. They can also flawlessly review the financial portfolios of clients to assess risk. Machine learning helps investors to devise advantageous investment plans by predicting the highs and lows of stock values.

 

Marketing: Lots of marketing and sales companies have already implemented machine learning systems to improve customer satisfaction. Today, they can analyze social media and e-commerce sites to identify the search and buying history of customers and make recommendations based on those. Many experts assume that the future of this industry will be heavily driven by machine learning as the systems will become more efficient at gathering, analyzing, and utilizing data to provide individuals with more personalized shopping experiences.

 

Agriculture: Machine learning applications help to accurately analyze weather conditions, field conditions, and crops to give better insights into different hindrances in agriculture. These systems are also helping in maintaining crop quality by aiding in better soil and water management.

 

In addition to these, industries such as education, manufacturing, advertising, food, healthcare, etc. are also benefitting from machine learning.

 

Top present and future jobs in machine learning

For those, who want to pursue a career in machine learning, here’re the jobs that are in high demand not only today but will remain so in the future as well.

 

Machine learning engineers: These people program machine learning systems to intelligently perform tasks. They’re highly skilled in various programming languages such as Java, Python, etc, and work with massive amounts of data.

 

NLP engineers: NLP is the short form of natural language processing that enables machines to comprehend human language. NLP engineers help to develop machines that are capable of understanding patterns of speech and translating verbal words into various other languages. In addition to machine learning skills, these professionals have a solid knowledge of grammar, syntax, and spelling of a minimum of one language so that they can train a machine the same.

 

Human-centered machine learning designers: The job role of these professionals revolves around developing systems that can recognize patterns and process information based on the available data. Netflix and YouTube are two such examples where the platforms offer suggestions based on viewers’ preferences.

 

Apart from these, professionals like data scientists, robotics engineers, big data engineers, and business intelligence developers are also anticipated to remain sought-after in the upcoming years.

 

Why parents should introduce their kids to machine learning

As machine learning appears with the potential to revolutionize the way we interact with technologies, a lot of companies have already started hiring experts in the field. In the future, this demand will be even greater with more businesses embracing this disruptive technology. If you’re still hesitating about whether or not you should introduce your child to machine learning, the following reasons could help make up your mind.

 

Helps to learn to code: Coding is an inherent component of machine learning and thus, your kids will automatically get introduced to coding when you introduce them to ML. Coding is one of the most sought-after job skills that open up a plethora of opportunities. Additionally, learning to code would help them develop logical thinking and mathematical reasoning which will become extremely beneficial for their future professional life even if they don’t pursue a career in machine learning or become a programmer.

 

Helps to develop data fluency: We’re heading toward a future that will be shaped by data-driven methods. In their effort to learn machine learning, kids will understand how gathering and analyzing datasets could help them land them a rewarding job in the era of big data. Every kid may not become a data analyst or a data scientist but they will become familiar with data processes, which will be almost essential in the future job market.

 

How to start teaching kids machine learning

Here’re some simple yet effective ways that parents can use to introduce their kids to machine learning.

 

Use applications: Coding applications like Tynker and Scratch let kids utilize prewritten coding instructions to help them develop algorithmic thinking. To help your kid learn the fundamentals of machine learning, you can use resources such as Machine Learning for Kids, Apps for Good, etc.

 

Use online courses: This is probably the best method when you are trying to introduce your kids to machine learning. Cutting-edge online courses on machine learning are designed to help kids obtain a robust foundation in technology. Some top-tier institutions also offer coding workshops so even if your kid doesn’t know to code, he/she can start from scratch.

 

Machine learning has the potential to transform many aspects of human lives for the better. It has the responsibility of parents to act now and start preparing their kids who could be the ones contributing to future developments in the field.