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Ritika Singh
Ritika Singh

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2019 Technical Overview & 2020 Top Trends Of Machine Learning


2020 has approached! It's time to welcome the new year with a touch of machine learning sprinkled with our brand new resolutions. Machine learning will continue to be at the heart of what we do and how we do it.

And what about 2019? What a year it has been! The large amount of development we have seen in natural language processing (NLP) has blown us away. It was the year of language models and development frameworks such as Google's BERT and OpenAI GPT-2 (more of that later!).

What we loved in 2019 was the community’s embrace of open source releases. They have further lowered the barriers to access to machine learning because more and more people in the community aim to break into this area in 2020. Here are all your ambitions and this wonderful career choice!

So, as we prepare for the New Year, we wanted to take some time and write this extensive and challenging article. We will look at the main developments in machine learning in 2019 in a technical way. We will also look at what we can expect from the different areas of machine learning in 2020.
Areas we’ll cover in this article
• AI and ML for Business Leaders
• The Matter of Ethics in Machine Learning
• Machine Learning Trends in 2020


The rise of machine learning has disrupted multiple and diverse industries across the globe. In fact, our job roles and functions are getting impacted to a large extent right now.

Executives, leaders, and CEOs are lining up to integrate machine learning solutions in their organizations. This was almost impossible a few years ago when businesses had to do a lot of things manually infrastructure wise. It’s no coincidence that machine learning projects had a higher chance of failure in 2015 than in 2019.

This uptick in machine learning investment has happened thanks in large part to the rise of cloud-based platforms. Yes, we’re talking about Google Cloud Platform, Amazon Web Services & more. These platforms have made adopting machine learning far easier than before. Thanks to their out-of-the-box solutions.

Let’s look at a few hardcore numbers by Forrester (taken from their report here ):

  1. 53% of global data and analytics decision-makers say they have implemented, are in the process of implementing, or are expanding their implementation of some form of machine learning.
  2. 29% of global developers (manager level and up) have worked on machine learning software in the past year (that’s a BIG number).


So how do we see 2020 planning machine learning? The current level of investment and interest in this area will only intensify! This is great news for all machine learning enthusiasts and novices hoping to pursue a career in this field.
Picking the top trends from the Forrester report we mentioned above:
• 25% of Fortune 500 will add AI building blocks (for example, text analysis and machine learning)
• In 2020, senior managers like Data and Analysis Directors (CADOs) who are serious about machine learning will ensure that data science teams have what they need in terms of data
• Expect a new peak in AI funding in 2020!


Data is the engine of every business and enterprise in the world today. Below is the potential to constructively channel its direction to achieve harmonious growth. On the other hand, there is also great potential for its leadership to become a mode of destruction for the masses. Everything is in our hands, so let's use the power of machine learning constructively for good.

Ethics is not widely spoken in the field of machine learning, as people often assume that a computer cannot be biased, prejudiced or harbor stereotypes - right?

Not true! The machine learning techniques themselves may be unbiased, but once we populate the data, assumptions, etc., there is a good chance that biases will appear in the model. The reason? These are conditions set by us humans that can project their bias into results, even if they did not intend to (unconscious bias).


We have covered many trends in this article! Here are some key trends that Analytics Vidhya forecasts in 2020 that we haven't covered in this Article:

• The number of machine learning jobs will continue to increase exponentially in 2020. Thanks in large part to NLP developments, many organizations will seek to expand their teams to employ NLP experts. The best time to enter this space
• Regarding jobs, we believe that the role of a data engineer will become even more important. Building machine learning pipelines is not an easy task - and amateur scientists are not exposed to this side of the life cycle. A data engineer is crucial to a machine learning project and we should see that this is reflected in 2020
• AutoML - It took off in 2018 but did not quite reach the heights we expected in 2019. Next year we should focus more on that, as standard AWS and Google Cloud solutions will become even more important.
• Will 2020 be the year when we finally see the breakthrough in reinforcement learning? It has been in the doldrums for a few years now because the transfer of research solutions to the real world has proven to be a major obstacle. We hope to see this trend change in the coming months!

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