Machine Learning Masterclass #4: Tools And Applications
Machine Learning has become an integral part of day to day life, particularly in the Digital World. Companies such as Google, Facebook, Netflix, and Amazon now use Machine Learning to continually update their services and algorithms. So far in this series, we have explored the basic principles, current applications and potential use of Machine Learning in SEO and Social.
In this blog, we will look at some of the tools and applications that are actively being used in the market. The Machine Learning solutions below range from easy to use off-the-shelf solutions to code-heavy custom built solutions and platforms.
Off-the-shelf solutions: IBM Watson marketing
IBM’s Watson is one of the earliest promoter of Machine Learning, made famous by its appearance on the popular quiz show Jeopardy. In Jeopardy, IBM comprehensively beat the human competitors, displaying capabilities of natural language processing and deep learning; key algorithms in Machine Learning.
Since 2011, IBM has expanded Watson’s capabilities much beyond Jeopardy. You can read about these here. For the digital marketeers, however, Watson’s suites of marketing solutions are highly useful. Using Watson marketing you can discover insight without having to invest into coding or hiring an expert data scientist. Simply said, the user-friendly interface of Watson marketing will allow you to utilise Machine Learning for your next marketing move without much pain.
GUI based machine learning solutions
If IBM Watson is too high level, lacks customisation, locks you with a set supplier, or simply hurts the sentiments of your slightly technical team :), then you can explore a few Graphical User Interface solutions with minimum coding skill requirement. You do need to brush up your knowledge of statistics and Machine Learning algorithms though.
There are a few options being discussed in this Quora thread. Amongst the solutions available, we believe KNIME is particularly user-friendly and easy to get started. KNIME works on the principle of creating workflows using plugins. The workflows are essentially Machine Learning models that can be assembled by simply dragging and dropping from the menu.
For example, the workflow above shows how you can perform sentiment analysis just by dragging and dropping KNIME plugins.
Google cloud platform and Tensor Flow
Lastly, if you are really in the mood to roll up your sleeves and dig deep (pun intended) then you have the very comprehensively assembled Google cloud platform. Using the Google Cloud Platform you can build and host applications and websites, store data, and analyse the data with the help of Google’s scalable infrastructure.
Within this platform, there is the Cloud Machine Learning with pre-trained models coupled with the ability to generate your own custom models. Using the service you can carry out text analysis, speech recognition, image analysis etc.
On top of the cloud infrastructure, Google also released TensorFlow. Simply said, TensorFlow is an open source library of Machine Learning codes. Using TensorFlow you can build and train deep neural networks (a computer system modelled on the human brain and nervous system) to detect and decipher patterns and correlations.
Just like cloud computing, Machine Learning is expected to become a norm. This means in the near future it will become impossible to avoid it as a marketing/analysis activity. Until that time comes, it is important to continue preparation, and either source the services from expert suppliers or build the skills in house. This blog should have given you a taste of the type of tools and services available out there, and what skill you would possibly require to get started.
If you are keen to discuss possibilities of Machine Learning services in your company then feel free to talk to one of Tamar’s digital marketing experts.