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Should Web Developers learn machine learning?
Given the growth and the impact of Machine Learning in our world today, it is a great advantage for web developers to learn Machine Learning.
In today’s insight, we are going to look at Machine Learning and Web development in order to help us understand whether Web developers should learn Machine Learning or not.
Machine Learning is huge in our world today, there are equal fears and excitements around it.
Machine learning is a method of data analysis that automates analytical model building.
It is part of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Machine Learning and Artificial Intelligence have huge applications in Education, Healthcare, Finance, transportation, sports, Economics, and many other fields.
Data science is the most common path to take if you can to work on Machine Learning and Artificial Intelligence.
But what if you are a Web developer, should you learn Machine Learning? Let us find out
HOW WEB DEVELOPERS USE MACHINE LEARNING
There are many great advantages to learning Machine Learning as a Web Developer.
This can be an intimidating task for many, but the ultimate results will be amazing.
Here are some of the reasons why Web developers should learn Machine Learning.
MAKING REAL-TIME CHATBOTS
As a web developer, you can use machine learning and Natural Language Processing to develop Real-Time Chatbots that you can integrate into your Web Applications.
These chatbots can help with automating customer services.
CUSTOMER RECOMMENDATION ENGINES
You can employ the power of Machine Learning to help customer product recommendations for E-commerce websites.
This will drive more engagement, sales, and growth.
Using Machine Learning, you can program your web application to know when the user is becoming less interested in your application and suggest ways to fix it based on the user’s interaction with your platform.
Machine Learning can help web developers to implement fraud detection on Web Applications.
This can be achieved using Machine Learning’s ability to understand patterns.
Whenever an activity falls outside that pattern, you can be alerted.
Using Machine Learning, your Web application can recognize places, people, and other objects.
Facebook uses Deep Face (Their ML image recognition project) to recognize a face, identify people in a picture, and suggest tagging them.
A web developer can use machine learning to add speech recognition to their applications.
This can be speech-to-text or performing different activities using speech instructions.
At a more complex level, Alexa, Cortana, Google assistance, and Siri use speech recognition technology to work.
EMAIL SPAM FILTERING
In an age of email marketing and communication, Email spam has become rampant.
To combat this, A web developer can use machine learning to filter spam emails and detect malware.
Gmail uses filter technology to classify emails as normal, important, or spam.
There are many other fields where a web developer can apply machine learning such as traffic prediction, Language translations, stock market trading, etc.
We can see that learning Machine Learning as a Web developer can be a great advantage and a chance to work on cutting-edge technology.
Learning Machine Learning as a Web Developer will also add more value to your resume and can help you land a good job in a big corporation.
MACHINE LEARNING PLATFORMS FOR WEB DEVELOPERS
To put the icing on the cake, there are many platforms and frameworks available to help web developers work on machine learning models.
Here are some of the frameworks that web developers can use for machine learning:
TensorFlow “is an end-to-end open source platform for machine learning.
It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in Machine Learning and developers easily build and deploy ML-powered applications.”
Tensorflow was developed by the google Brain Team in 2015, It is written in C++, Python, and CUDA.
MICROSOFT COGNITIVE TOOLKIT
The Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning.
It describes neural networks as a series of computational steps via a directed graph.
It was developed by Microsoft Research in 2016 for Windows and Linux. It was written in C++ and Python.
The Microsoft Cognitive Toolkit (CNTK) can be included as a library in your Python, C#, or C++ programs making it easy to integrate for Web developers working with Python or C#.
Apache SINGA is an Apache Top Level Project, focusing on distributed training of deep learning and machine learning models for web development.
SINGA has a well-architected software stack and easy-to-use Python interface to improve usability.
It was developed by the Apache Software Foundation in 2015 for Linux, macOS, and Windows. It was written in C++, Python, and Java.
There are many other frameworks such as Caffe2, Apache Mahout, etc. that you can use as a web developer to work on machine learning applications.
Web developers should endeavor to learn machine learning to keep up with the changing times.
However, you are not any less of a web developer if you do not learn machine learning.
Web development in itself is a huge field and there is so much to keep up with.
Learning Machine Learning for Web Developers is not a necessity but it can be very helpful in our times today.
Learning Machine Learning as a developer can also help to set you apart from other Web developers.
There are very few employers if any who would resist hiring a Web developer who understands machine learning.
If you would like to learn more about machine learning, check out the Udacity Nanodegree