Machine Learning
“Whether a piece of fruit in a photo is a banana or an apple, spotting people crossing the road in front of a self-driving car, whether the use of the word book in a sentence relates to a paperback or a hotel reservation, whether an email is spam, or recognizing speech accurately enough to generate captions for a YouTube video.”
(Heath, 2020)
The backbone to the artificial intelligence responsible for a lot of services you use daily is data.
For example, “recommendation systems like those on Netflix, YouTube, and Spotify; search engines like Google and Baidu; social-media feeds like Facebook and Twitter; voice assistants like Siri and Alexa.” (Hao, 2020)

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There are 3 common types of machine learning:
- Supervised learning — the algorithm is told to find specific patterns
- Unsupervised learning — the algorithm is looking for any pattern
- Reinforcement learning — working towards a pre-determined goal through trial and error
Gartner describes AI techniques such as Machine Learning to be the number 1 trend by 2024 in organizations, with an estimate of 75% of organizations using it. (Gartner identifies top 10 data and analytics technology trends for 2020)
GlobeNewswire forecasts the value of the Machine Learning industry to reach USD 117.19 Billion by the end of the year 2027. (Fortune Business Insights, 2020)
So, who can use the technology?
No matter which industry you work in or plan to enter, machine learning will most likely be able to serve your objective using data. Whether the data is from healthcare, Youtube, business, agriculture, finance, or banking sectors, Machine Learning can automate the process of analyzing the data to work towards your objective. Where there is data, there are patterns and context, and Machine Learning will aid in deducing relevant variables.
What does my enterprise need to use Machine Learning?
Structured data and a purpose!
Who can conduct Machine Learning for my enterprise?
A data scientist or a Machine Learning Engineer.
Enterprises interested in the use of this technology will be greeted with a market at great competition, Enterprises can opt into the use of vendor solutions or they can opt to use open-source technology.
Paid-for solutions such as Microsoft Azure Machine Learning Studio is a GUI tool advertised to “construct and operationalize Machine Learning workflow on Azure” https://studio.azureml.net/
Open-source tool from Google called TensorFlow provides open-source Machine Learning platform https://www.tensorflow.org/
References
- Gartner identifies top 10 data and analytics technology trends for 2020. (n.d.). Retrieved March 01, 2021, from https://www.gartner.com/en/newsroom/press-releases/2020-06-22-gartner-identifies-top-10-data-and-analytics-technolo
- Hao, K. (2020, April 02). What is machine learning? Retrieved March 01, 2021, from https://www.technologyreview.com/2018/11/17/103781/what-is-machine-learning-we-drew-you-another-flowchart/
- Heath, N. (2020, December 16). What is machine learning? Everything you need to know. Retrieved March 01, 2021, from https://www.zdnet.com/article/what-is-machine-learning-everything-you-need-to-know/
- Insights, F. (2020, July 17). Machine learning market to REACH USD 117.19 billion BY 2027; increasing popularity of self-driving cars to propel demand from automotive industry, Says FORTUNE BUSINESS INSIGHTS. Retrieved March 01, 2021, from https://www.globenewswire.com/news-release/2020/07/17/2063938/0/en/Machine-Learning-Market-to-Reach-USD-117-19-Billion-by-2027-Increasing-Popularity-of-Self-Driving-Cars-to-Propel-Demand-from-Automotive-Industry-says-Fortune-Business-Insights.html