All you need to know about Machine Learning-
What is Machine Learning?
As humans, our ability to learn and get better at tasks through experience is part of us. When we were born, we almost knew nothing and can do almost nothing for ourselves. However, gradually we become more capable every passing day; likewise, computers can do the same.
Machine Learning can bring statistics and computer science together to enable computers to learn and adapt to the tasks given, just as our brains learn from past experiences.
In simple terms, Machine Learning, as the name suggests, is a process where machines learn and analyze the fed data and predicts the outcome.
“Any sufficiently advanced technology is indistinguishable from magic.”
- Arthur C. Clarke
Machine learning is the most contemporary innovation that has helped man evolve industrial-wise and professional processes and advances in everyday living.
Why Machine Learning?
Machine learning is all around us, from Facebook’s feed to Google Maps for navigation. So it is pretty hard to ponder over any industrial activity that can be done without machine learning.
The incredible ability to adapt and provide solutions to complex problems efficiently, effectively, and immediately. Machine learning is applied in our everyday lives, as Apple’s Siri responding to our queries, facial recognition, Online recommendation engines from Facebook, Netflix, and Amazon. It would be pretty hard for us to perform the tasks mentioned above without using machine learning.
“Just as electricity transformed almost everything 100 years ago, today I have a hard time thinking of an industry that I don’t think AI will transform in the next several years.”
- Andrew NG.
How do we get machines to learn-?
Humans learn from experience and so do machines. The simple technique behind learning is to make a computer learn a task; we give it a set of questions followed by an answer.
Machine Learning is an integral part of resonating with everyone these days; however, various approaches to getting machines to learn from basic strategies to layers of artificial neural networks.
While choosing the best learning algorithm is often emphasized, scientists and researchers have found that some of the most interesting questions arise from none of the available machine learning algorithms.
Machine learning uses data to answer questions, using the data referred to as training, while answering questions is referred to as predicting an outcome or inference.
In brief, training utilizes the given data to inform the making and fine-tune for a definite predictive model. Further, this predictive model can then serve predictions on previously unseen data and answer those questions. Thus, gradually, as more data is gathered, more projections can be improved over time.
Image source- AIAdentures
How Machine Learning is changing the world
Machine Learning today has some aspects of human abilities but certainly not the real potential for human intelligence. Machine learning acts as a catalyst in enabling people to accomplish more by collaborating with intelligent software. More human face to technology is what it is.
Machine learning is transforming the world by enhancing all segments, including healthcare services, education, transport, food chain, entertainment, and many more. Machine learning will impact lives in almost every aspect, from housing, shopping, food ordering, cars, etc. Further offers potential value to companies trying to leverage big data for customer satisfaction.
Business benefits of Machine Learning-
- Terminates Manual Data Entry:
Machine learning and predictive modeling algorithms can significantly avoid blunders caused by manual data entry. Machine learning programs make these processes better by using the discovered data. Consequently, the employees can manage the tasks that add value to the business.
2. Online recommendations:
Machine learning is a mighty tool that can propel your business to the next level. For example, most e-commerce websites use machine learning for product recommendations, similar product recommendations as ‘You may also like’ or suggestions for accompanying goods like ‘Frequently bought together.
Algorithms use the customer’s purchase history and match it with the extensive product inventory to distinguish hidden patterns and similar group products. Further, these products are then recommended to customers persuading product purchase.
3. Scam detection:
Spam filters are creating new rules by utilizing neural networks and statistical models to classify data. For example, while spam is detected, a trained machine learning model must determine whether the sequence of words found in an email is similar and closer to those seen in spam emails or safe ones.
Email spam has become a significant problem nowadays among internet users. Therefore, it’s high time to incorporate machine learning modules to detect spam and make emails easy.
4. Image recognition:
Image recognition can produce symbolic and numeric information from images and other high-dimensional data known as computer vision. Data mining, Machine learning pattern recognition, database knowledge discovery are all included.
Machine learning in image recognition is a prominent aspect and used by various industries, including Automobiles, Healthcare, etc.
5. Customer’s Value Prediction:
The major challenge faced by marketers is customer value prediction and customer segmentation. With the help of data mining, machine learning can be accessible in business to predict customer behaviors and purchasing patterns and help customers individually send the best possible offers, all based on their browsing history and buy taste.
Real-life examples of Machine Learning-
1. Virtual Handy Assistants-
Google Now, Alexa, Siri are some of the favored virtual assistants personally used by individuals. They assist in finding information when asked vocally. Once activated and asked upon, “What is my schedule for today?”, “What are the flights from London to the USA?” “Call mom,” “Set an alarm at 6 AM,” or similar ones. Now for answering this, the assistant looks out for the information, recalls related queries, sends commands to other resources to get information.
We got to accept that owning a personal assistant is a big solace!
2. Traffic Alerts-
How does Google Maps know that you are on the fastest route although the traffic is high?
It is a combination of multiple factors like historical data of the route, how many people are currently using the services of Google Maps, and some real-time techniques. While using Google maps, you allow the app to use data like-
· Your location
· Your average commute speed
· Day, Time, and any specific occasion
Hence, using this data, AI and Machine learning algorithms make accurate conclusions and give you the exact information.
3. Social Media Services-
From better ad targeting and personalizing news feeds, social media platforms use machine learning for their user benefits.
· People You May Know- By Understanding experiences, Facebook notices the friends list, profiles recently visited, interests, and such. Then, based on past searches and continuous learning, Facebook suggests a list of users.
· Face Recognition- Once you upload a picture with a friend and immediately, Facebook recognizes that friend. Further, Facebook checks the projections and poses in the picture and matches them accordingly with the people in the friend list.
· Matching Pins- Pinterest uses computer vision to identify the pins in the images and recommends matching and similar pins accordingly.
4. Google Translate-
When you travel to a new country, the experience is surreal and thrilling; however, the language takes the back seat. As a rescue factor, Google Translate helps. Google utilizes ‘Google Neural Machine Translation,’ which has the ability to collect numerous languages, words and transmute the sentence to the desired language.
5. Online Video Streaming Apps-
Netflix and Amazon Prime are pioneers of video streaming. These apps capture the data of the user’s activities and gush out video suggestions. A few aspects like-
· Content genre
· Browsing pattern
· Survey after watching a movie or series, asking whether you liked it or not, is considered.
Based on these considerations, Machine learning modules, and applications, businesses can engage their audience by providing recommended and top-notch streaming experiences.
Key Takeaways in Applying Machine Learning-
Machine learning uses algorithms, which can help enhance business scalability and improve business operations when it comes to business. This is achieved by an amalgamation of both AI and ML. For example, today, ML models can predict nearly everything from highs in web traffic, disease outbreaks, stockpiles and product recommendations, hardware failures, bugs, spam detection, and traffic patterns.
- Takeaway #1 Machine learning helps unlock the data. Also, forecasting improves customer engagement, helps to expand into new sales channels, reduces inventory, improves productivity, and creates more precise demand forecasts better.
Machine learning uniquely handles the velocity of data generated by a new delivery process.
- Takeaway #2 With Machine Learning, everything is changing from manual to automatic. Automatic tasks, more exact results, and faster results can all be executed.
- Takeaway #3 Tools used for Machine Learning like Spark and Tensorflow support the growth and accelerates machine learning. Also, AWS does provide a complete portfolio of tools and services for producing AI applications with machine learning. Azure and Google follow similar options for adapting machine learning algorithms.
The future of Machine Learning-
Machine learning can be a cut-throat advantage to any niche, from MNC’s to startups. However, as automation increases, Machine learning will continue to improve. Also, data scientists and ML engineers will focus more on building great models and spend less time on the necessary tasks surrounding production ML systems.
Wrap up-
Machine learning is unique in its way. In contrast, experts raise several concerns over the presence and ever-increasing dependence of machine learning. On the other hand, the world is witnessing the magic in healthcare, the finance industry, image recognition, image processing, and various other fields.
Although we may be skeptical about machines taking over the world, it is totally up to us to develop practical yet safe and controlling devices. Machine learning is a significant boon for us, and no doubt it would change how we do many things, including education and healthcare services transforming the world into a safer and better place.
