Machine Learning is the field of computer science where the machine learns the pattern from the user's input data and tries to classify or predict the output.
How does Machine learn?
When we start hearing about machine learning, this question may arise for all of us. Let us explore this, the researchers and mathematicians designed Machine learning Algorithms so that they can observe the patterns from the data and it can predict the correct output on new data. There are many algorithms like Linear Regression, Logistic Regression, and many more we can discuss more this later
Types of Machine Learning
- Supervised Learning
- Unsupervised Learning
- Semisupervised Learning
- Reinforcement Learning
In this blog, we can focus more first two types
Supervised Learning :
In this type, the output will be given or otherwise Labeled Data Machine Learns from the data and output and tries to predict on any new data. For example, when we were children we learned new things by asking a question from our parents or elders they give us the required output and we learned from that which is similar to that this is all about supervised machine learning.
Unsupervised Machine Learning
In this type, output will not be given or Unlabeled Data will be given a machine tries to form a pattern and predict the output this is all about Unsupervised Learning
