Hello
Everyone! We have started this blog fully dedicated to Machine Learning and We
will post articles step by step to take you through different machine learning
algorithms and technologies.
Machine
Learning is field in computer Science that grew out of Artificial Intelligence.
Tasks like autonomous driving, speech recognition, image recognition, Spam
filtering are nearly impossible to program but can be done through machine
learning algorithms.
These
algorithms and field have been extensively used in the fields like Natural
Language Processing, Medical Diagnosis, Autonomous Systems, Cyber Security,
Image Recognition, Web Mining, Astronomy etc.
Machine’s getting ability to learn…
Simple flow
for developing machine learning model is
Get Data -> Train Model ->Evaluate Model…
Machine
learning is impossible without abundance of data but luckily there has been
explosion of data nowadays and we have plenty of data in most of the fields.
These are basic resources for creating machine learning models.
These data
are used to train the model. Its teaching our model with lot of examples and
let model figure out how to produce result for new data.
After we train the model, Evaluation is like
taking exam of model. The model gets new unseen data and does some calculations
and then produces output. Evaluation step scores performance of the model only
then we can then say how good is the model.
Supervised
Learning
- Learning where model is trained with right labels or correct answers already given i.e teacher signal is associated while training
- Example problems Classification, Regression, SVM.
Unsupervised
Learning
- In this learning model produces some structure from unlabeled dataset.
- Example Clustering.
We will go
into detail of various algorithms and technology in next articles.
