Machine Learning: A Beginner’s Guide  

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Our life has become so much dependent on technology, the soul of technology is data.  

 Anything that we see on the internet comprises a generous amount of data, but unfortunately, humans are not equipped to analyse such a plethora of data at once. That’s where machine learning comes to the rescue by interpreting the data and making our lives easier.  

 Now that you have a basic understanding of machine learning, keep reading to know more.  

 

Machine Learning: In A Nutshell 

 In simple terms, machine learning delivers resourceful interpretations by analysing data to make informed decisions on a certain subject. Although machine learning is a part of the artificial intelligence spectrum, it plays a slightly different role related to technology. Usually, there are several data and algorithms involved in the use of machine learning.  

 To give further context, machine learning is broadly classified into three functions – to predict what will happen, prescribe what can be done, and describe what has happened. For instance, if a problem arises within the AI spectrum, machine learning will analyse the data and respond accordingly with an appropriate solution. 

 

How does machine learning work? 

 The sole purpose of machine learning is to analyse and understand patterns from a plethora of data and make appropriate predictions. This way, machine learning will compare different predictions to derive accurate results and help in improving the function of the product.  

 As mentioned earlier, one of the prime objectives of machine learning is to improve predictions through data and avoid unwanted disruptions in the development of the desired product.  

 Over the years, machine learning has majorly created an impact across the world with artificial intelligence in several industries.  

Popular real-life examples of machine learning: 

Now that you have understood the idea behind the working of machine learning, let’s have a look at some of the popular examples of machine learning used in everyday life: 

• Interactive chatbots – Almost every brand uses chatbots to interact with potential customers to answer customer queries, provide solutions, and help in customer service. AI chatbots can read the phrases, identify the keywords, and respond. AI bots can handle customer queries 24/7 without human intervention.

 

• Image detection helps in extracting instant information from several images. For instance, Google Lens uses AI and machine learning, to find relevant information for the users. 

 

• Fraud prevention can be handled with the help of machine learning by analysing the data and figuring out the cause of the problem and preventing it from happening again. 

 

• Personalize Everything – like offering recommendations, curating a personalized feed, and giving suggestions on what to watch or order next. Examples of companies that use such resourceful ML-based algorithms are Netflix, YouTube, Instagram, and Zomato. 

 

• Medical Image Processing is one of the most complicated areas where machine learning plays an important role because often such details of the human body are not visible to the naked eye and helps medical professionals to better perform surgery and medical research. 

Therefore, without realising, all of us are using machine learning in some way, like calling Alexa, attending Google Assistant, getting suggestions on Facebook, etc.  

 

Final thoughts 

 ML & AI are growing at a rapid phase and provides tools and strategies to this generation of customers to analyse and interpret a large amount of data to solve several day-to-day problems.  

 If you need any help with implementing the latest technology including AI/ML, reach out to Ticvic. We offer several services like custom software/application development in the USA and India.  

 Connect with us and we can help with everything related to IT.