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Boosting Your Startup Idea Using Machine Learning Applications

Machine learning is the creation of algorithms and systems which self-learn by processing and analyzing the data. If we look around this technological era, we see products of Machine learning in self-driven cars, facial and speech recognition, and even contextual web search. So how can machine learning assist your startup?

Machine learning can be very fruitful for a start-up but for that to happen, “data” should be used as the key for creating an effective machine learning system. The machine gets better, profoundly diverse, and more potent than other systems if more and more data is fed into it. A basic example could be, a Facebook news feed, which shows people the targeted ads and feeds from friends/pages, based on what content they posted or even “liked” on Facebook.

Four Machine-learning Areas

There are four different Machine-learning zones, which can be used by start-ups or businesses:
  1. Supervised learning: This method, hand holds the machine to teach it and then leaves it on the machine itself to learn and give results from unprocessed data fed to it. For instance, an algorithm that identifies a picture as a “face”, first need to be taught what a face is. For this the data must be labeled and should explicitly show what a face is and what is not. After such training of algorithm is completed via a large set of data, the algorithm is then capable to process unstructured, unlabelled data.
  2. Unsupervised learning: This method lets the algorithm self-learn by trying to find the hidden meaning through clustering similar patterns of unlabelled data. A good example can be Google, where numerous connected computers analyze over 10 million videos and identify dog faces using Meta tags and descriptions, without being told upfront about what a dog's face looks like.
  3. Reinforcement learning: This algorithm learns by trial-and-error search and a delayed reward. The program is not told what results are expected, while the algorithm has to discover by itself which results yield most rewards by trying them.
  4. Deep learning: This machine learning process used big data to work. The program is taught to think hierarchically and more contextually by using neural networks.

Examples of Machine-Learning

Machine learning is more of creating another “artificial brain” to assist you in daily activities. The best example could be Apple’s Siri, Microsoft’s Cortana, and even Facebook’s facial recognition technology.

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Machine learning thus helps in better customer engagement, the more a product knows about its customer, the more successful it is. Each example cited above has one thing in common, their algorithms get better as more and more data is fed into them by regular usage.

So, how could Machine Learning be useful to a Startup?

In the case of start-ups, the company has a limited understanding of their customer and market. Using the existing data and trends, they can take the help of machine learning to understand their customer base and demographics. The machine learning system would keep improving its results, day in and out, giving better information and insights to start-ups, helping them grow at a rapid pace.

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Among, several possibilities, one of the best advantages is recommending the right product to the right customer at the right moment. The medical industry can use Machine learning technology to identify symptoms a patient has and thus assist doctors for correct diagnosis and hence providing precise medicines. Further, trade prices of US corporate bonds can be predicted or employee attrition can be curbed by incentivizing employees by depicting their online behavior.

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There are endless possibilities for machine learning and it will result in smarter systems and intelligent humans as well. The examples cited above for facial or speech recognition or even mobile assistant is just the beginning, while a plethora of ideas lay ahead for a great new technological world of start-ups.