Basics of Machine Learning [Infographic]

A Look at Machine Learning Infographic

Machine Learning is a field of Computer Science which allows Machines to learn. This learning is based on data and stats collected through various sources. Once trained the machines are then able to perform various tasks without human intervention.

It is a need for a Digital World where everybody wants to automate things. With the help of Machine Learning, we can build algorithms that can replace human efforts.

The main way through which these algorithms could be trained is to provide data having patterns. These patterns could be used to take future decisions. Same way Human beings take decisions based on the pattern and Human intelligence.

Even the learning process is automated with the moderator providing annotations for better learning. Now there are different types of Machine Learning. We will be looking at them after you have gone through this Machine Learning Infographics.

This Infographic will guide you into the basics of this field and how things actually work.

So according to the Infographics here are the steps involved in Working of Machine Learning:

  1. Select Data – Splitting the data into three groups as Training Data, Validate Data, and Test Data.
  2. Model Data – Building a model based on the training data with available tools and technology.
  3. Validate Model – Assess the model with feedback inputs using the Validate Data.
  4. Test Model – Test it with your Test Data
  5. Use The Model – Now use your model for predictions on a new data set.
  6. Tune The Model – Adjust parameters, add more data, update features to tune the model

There are three main types of Machine Learning as describes below:

1. Supervised Learning

This type of learning includes already collected and stored data. The data is present with input values and a target label set. This target label set guides the learning process and helps in training the models.

2. Unsupervised Learning

In this type of learning, there are no target labels provided with the data. The learning is based on incoming patterns which are then molded into classes. These classes can then be used for future predictions and learning.

3. Reinforcement Learning

This type of learning involves rewards for every good or bad decision that the model takes. The reward could be positive or negative as per the decision. If the model takes a bad decision then it is rewarded with negative feedback and vice versa.

So this was some basic information taken from the above Graphical representation. Do share it with someone that needs to know about it.

Machine Learning Infographics From Pwc 

Disclaimer: The information provided in the Machine Learning Infographics are the views of its creator. Present Slide takes no responsibility for the reliability or correctness of the information stated in the Infographics. We neither own the content nor do we pretend to own it.

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