Machine Learning

What is Machine Learning? Everything You Need to Know

What is Machine Learning?

Machine Learning is one of the emerging technologies that is used to convert data into information. The age of the Big Data started a few decades ago when the use of digital media created an explosion of data. Businesses identified the huge potential in analysing the data and gaining insightful information. This need led to the development of Data Science, which in turn brought about the development of Artificial Intelligence. A subset of Artificial Intelligence is Machine Learning. This advanced technology empowers machines with the capability to self-learn. This means that the machine can be “trained” to do a whole suite of tasks. Machine Learning is now changing the meaning and application of automation.

Machine Learning tools and technologies are being applied across sectors. As this technology is still in the early stages, there is a huge scope not only for research and development, but also in operations. So, there will surely be a huge demand for skilled and trained ML professionals. Students and working professionals will greatly benefit by joining a machine learning course in Bangalore as a certification will improve your job prospects and enhance your career growth.

How Does Machine Learning Work?

How Does Machine Learning Work

The machine learning process includes the following steps:

  1. Data Collection – The primary step of an Machine Learning process is gathering relevant information from various sources
  2. Data Preparation – Once all the data is collected, it needs to be identified, sorted, and classified before analysing it. The techniques of data preparation depend on the kind of task that is to be done by the Machine Learning application.
  3. Training – This stage involves training the machine to self-learn from the analysed data. Learning algorithms are created based on various parameters and expected outcomes of the application.
  4. Evaluation – In this step, the Machine Learning application is tested to evaluate its performance and also identify bugs and find areas of improvement
  5. Fine Tuning – Creating Machine Learning applications is a continuous process. As data preparation and analysing techniques evolve, the algorithms and the Machine Learning application model need to be fine-tuned.

Machine Learning Techniques

There are 4 major Machine Learning techniques that you will learn about when you take up machine learning training in Bangalore. The major techniques are described as follows:

Supervised Learning

This Machine Learning technique aims to map rules that connect input and its output. Details of past inputs and outputs are provided to each labelled data. For example, details of footfalls during the different days of the week can be used to forecast the proposed number of visitors to a mall on any given day. One of the crucial factors of a supervised learning model is that the algorithm should be able to adapt to new inputs and maximize generalisations. A limiting factor of this model is that it exactly follows the examples. So, it is very important to show unbiased examples, or the model may not be fully functional. Classification and Regression are methods used in supervised learning.

Unsupervised Learning

In unsupervised learning, only the input data examples are provided. The algorithm is defined to identify different patterns hidden within the data and deliver different outputs. An example is to provide a pile of coins in different sizes and colours. The algorithm can classify the coins based on colours or sizes. The machine may find unsupervised learning harder to learn compared to supervised learning. Clustering, Anomaly detection, dimensionality reduction, and association are methods used in unsupervised learning.

Semi-Supervised Learning

This technique is a hybrid of supervised and unsupervised learning. Inputs are provided to all labelled data, but specified outputs are not provided to all the labelled data. This method reduces the need to have all data labelled, and gives the machine the flexibility to deliver different outputs. Generator and discriminator are two neural networks used in semi-supervised learning.

Reinforcement machine learning algorithms

This Machine Learning technique is a little complex and is based on the psychological rule of using positive and negative feedback to reinforce behaviour. It is suitable for use in rich data environments like that in video games. The simulated game environment can be developed based on positive and negative feedback received by gamers.

Why is Machine Learning Important?

In this digital era, Artificial Intelligence and Machine Learning are making huge waves of changes. Machine Learning is increasingly being used to automate processes. A lot of research and development is being done on Machine Learning-based applications such as smart power grid, smart homes, smart retail, precision farming, smart cities, and urban planning. In many applications, Machine Learning is used along with IoT (Internet of Things) to build a network of self-learning and self-operating systems. Machine Learning-solutions are also used to create self-correcting programs and automate repetitive tasks in a work process. This technology will play a great role in building the future. That’s why Machine Learning is so important in the current scenario.

Application of Machine Learning

Just like we discussed earlier in this blog, Machine Learning is important as it finds application across various sectors.  Augmentation, automation, and other Machine Learning applications are used in sectors such as:

Finance Industry

In the finance sector, machine learning tools and techniques are used for portfolio management, algorithmic trading, loan and insurance underwriting, risk management, document analysis, trade settlements, and high-frequency trading. These tools can also be used to detect frauds and prevent money laundering.

Government organizations

Governmental organizations have also realized the benefits of using ML tools and applications. There are plans to use ML solutions in urban planning and smart cities.

Healthcare industry

In the healthcare sector, Machine Learning techniques are used in imaging and diagnosis, patient data collection and follow-up, radiology and radiotherapy, drug discovery and experiments, disease identification, and online health consultation. Robotic surgeries are also being experimented in the healthcare sector.


Machine Learning is completely reshaping marketing, both traditional and digital. Machine Learning tools can be used to improve lead scoring, predict customer behaviour, build dynamic pricing models, perform sentiment analysis, prioritize customer personalization, build recommendation systems, and create chatbots.

Why Learn Machine Learning?

Learning Machine Learning is important because the future is in Artificial Intelligence and self-learning systems. The demand for Artificial Intelligence and Machine Learning-based solutions is increasing as more and more companies are moving towards this domain. Also, many industries are planning to use Machine Learning-based solutions to automate their work processes and enhance their work performance. All this points to the fact that there will be a huge need for certified and trained professionals in this field.

Whether you are from an IT background or a different domain and wish to build a career in Machine Learning, it is necessary to get certified in Machine Learning. You can join a machine learning course in Bangalore to upskill yourself. The intensive training will equip you with the knowledge and skills of Machine Learning tools, techniques, and applications.

The benefits of joining machine learning training in Bangalore are that you:
  • Learn from industry experts and subject matter experts
  • Learn the advanced tools and techniques in machine learning
  • Work on projects and assignments that are based on real-world situations
  • Build a network of like-mind people
  • Earn a certification from a reputed institute, which will improve your career prospects

What are the Job Opportunities in Machine Learning?

As discussed above, the scope for machine learning applications is high and is expected to grow in the future. With a certification in Machine Learning from a reputed institute, you can apply for job profiles such as:

  • Machine Learning Engineer
  • Data Scientist
  • NLP (Natural Language Processing) Scientist
  • Business Intelligence Developer
  • Human-Centred Machine Learning Designer
  • Computational Linguist

What is the Salary Package of Machine Learning Professionals?

The salary package for Machine Learning professionals depends on various factors such as experience, expertise, and certification. In India, entry level Machine Learning engineers can earn an average salary of up to INR 5 lakhs per annum. Professionals with up to 4 years of experience can expect to earn upwards of INR 7 lakhs per annum. Top management professionals with more than a decade or two of experience in the field can expect to earn up to INR two million per annum.

Who Can Join Machine Learning Course?

Professionals from the field of Data Science, Artificial Intelligence, Computer Science, IT, and other related fields can join a Machine Learning course in Bangalore. Graduate students in these domains can also take up this course to build a career in the Machine Learning domain. Professionals with a background in statistics and mathematics can also join machine learning training in Bangalore. However, they will need to learn the basics of coding, especially Python before they take up the Machine Learning course.

Why learn “Machine Learning” courses through Corpnce?

Corpnce offers in-depth machine learning training in Bangalore for working professionals as well as graduate students. The curriculum of our training program is integrated with the latest developments in this field. Also, we follow a project-based learning methodology. This means that aspirants who enrol in our training program will need to do mini projects as well as a large project as a part of their training. These projects and associated assignments will help students apply the learning to real-world situations. Corpnce also provides placement assistance for deserving students.

If you are interested in building your career in the Machine Learning domain, learn from the experts in the domain at Corpnce. Contact us to enrol in a batch today.