Machine Learning is a technologically evolved tool which utilizes machine intelligence to capture the untapped areas of business models. We at VM AFFLUENCE recognize Machine Learning as one of the pinnacle problem solving techniques for emerging and established businesses. Our expertise at Machine Learning helps businesses tap into the vast and unexplored reserves of unprocessed data and make informed decisions from them. Be it data mining, deep learning or analyzing or processing raw chunks of information, we can help you set up a formidable fortress of data supremacy.

What is Machine Learning?

Machine Learning is an essential embodiment of Artificial Intelligence. It deciphers and builds algorithms that allow computers to learn how to perform tasks from existing data. This reduces the workload of a programmer and enables him to focus on core tasks, rather than writing complex codes for the same. Machine Learning analyses previously available data and scans through millions of examples to come to a conclusion. With this intelligence, machines can understand complex patterns and predict outcomes to situations more accurately. In other words, “Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed.”


The scope of Machine Learning is infinite and when applied to existing business models it can dig up so much information which otherwise would seem impossible to extract and assimilate. At VM AFFLUENCE, we use deep learning, natural language processing and neural networks that can replicate human decision making and allow real-time applications of Machine Learning. Below are the possibilities that you can extract with machine learning.


1. Image tagging: The Machine Learning algorithms can identify faces or specified objects in a photo based on the photos that you manually tag. This can reduce redundant tasks for manual data operators.

2. Optical Character Recognition: The algorithms learn to identify a certain image as a written character and convert a scanned text document into a digital file for various uses such as data grouping and image processing.


1. Sentiment analysis: This method can be used to classify if the opinion expressed by the writer is positive, neutral or negative. This can be used for future marketing strategies and product development.

2. Information extraction: The algorithms can extract a particular piece of information such as names, web links, addresses, keywords etc.

3. Filtering: With Machine Learning, data can be classified as a tweet, chat, post, blog or spam posts. This can help firms which have huge inflow of social content on a daily basis.

4. Improved content discovery: With Machine learning, you get intelligence into what kind of content users are likely to follow and read and based on their interests and reading patterns, you can suggest articles that are aligned to their interest. In this way, you can create a more immersive and personalized experience for your users.


1. Predictions: Banking sectors can use this to analyse credit worthiness and probability of loan defaulters. Other applications include trading, building predictive models of prices and market volatility, portfolio management and risk management.

2. Anomaly detection: This technique is used for fraud detection. Companies can detect which transactions are outside the usual purchasing patterns of the user and warn them at an early stage. Also, retail and e-commerce websites can use these algorithms to block fake accounts.


Machine learning algorithms help to draw insights and predictions from the huge sets of data. It is not just about tracking user data but presenting it in a readable manner for decision makers to make critical business decisions. Data visualization is a very important aspect of machine learning and we at GoodWorkLabs create models that help to extrapolate this critical information into easy readable and understandable formats.