Basics of Machine Learning

Hi This is TechGecs 😄

Have you ever think if the human’s work can be done by machine? Is it possible???

The answer is Yes! Machine Learning is a technology through which machines can learn from their past experiences. Machine Learning is nothing but a subset of Artificial intelligence through which machines have the ability to learn itself and improve their performances by getting previous experiences without being explicitly(not done by the programmer) programmed.

Why Machine Learning?

That’s a very obvious question of why to learn machine learning. As we know, with increasing the businesses around the world, the data is also growing day by day.

Data is the soul of all business. Information driven choices progressively have the effect between staying aware of rivalry or falling further behind. AI can be the way to opening the estimation of corporate and client information and establishing choices that stay with an in front of the challenge. Machine Learning enhances business in different ways to get important information from raw data.

How Does Machine Learning Works?

There are several steps in between a model to make a prediction for the particular task by machine.

  1. Data Collection
  2. Data Preparation
  3. Choose a Model
  4. Train a Model
  5. Evaluate the Model
  6. Parameter Tuning
  7. Make Predictions

We are not going to describe these Technical terms and just take some time to understand the basic steps which use in ML.

There are several machine learning algorithms like Linear Regression, Logistic Regression, clustering, KNN, etc. on which model works.

Applications of Machine Learning

This is the main part of where you can understand how useful machine learning is:-

  • Oil and Gas Industry:

                                              This is maybe the business that needs the utilization of AI the most. Directly from dissecting underground minerals and finding new vitality sources to gushing oil conveyance, ML applications for this industry are tremendous are as yet growing.

  • Digital Marketing:                                                                                                                                                                                                                                                                                                                     Machine Learning can be used to making Digital Marketing strategies after getting much amount of useful data.
  • Healthcare:

                             As we know, Google already developed an algorithm to detect cancerous mamograms. Different universities are researching to make ML useful to treat diseases in very less time.

  • Businesses: 

                            In this, Business generated tons of data which may be useful or not, here ML makes sense to extract meaningful data from raw data by using algorithms and help to make better business decisions.

  • Face Recognition:

                                       This is a very interesting application of ML which really helpful to stop many terrorist activities. It uses at different places like Airport.

  • Recommender System:

                                                 Recommended videos and apps by using the machine learning algorithm in such an order that you like is basically an ML-based recommender system.

Steps to Become a Machine Learning Engineer

These are some basic steps that you can follow to become an ML expert.

  • Start by learning a programming language(mostly preferable Python or R).
  • Learn some Maths concept of Linear algebra, probability, statistics.
  • Grasp the concepts related to EDA and Machine Learning
  • Then learn and understand working ML algorithms.
  • Practicing in Kaggle or a different platform
  • Always keep Practising and doing research.

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