Thursday, 24 November 2016

Easy Steps to become proficient in Machine Learning:

Easy Steps to become proficient in Machine Learning:

In this post I would like to know you about an easy way of few steps to mastering into machine learning. Before that every one has few basic questions in their mind. Where to start? How to proceed?

Where to start learn ML? 

To understand this post, that is enough to have minimum knowledge on machine learning in Python.The main aim of this post is to know you about the freely available tools to in the market.

I am writing this post by assuming you are not an expert in

1. Machine learning
2. Python
3. Any of Python related machine learning like scientific computing(SCIKIT), or data analysis libraries

Tuesday, 22 November 2016

What machine learning algorithms can be suitable for data and images?

What machine learning algorithms can be suitable for data and images?

In this post I would like to give brief idea about when to use which algorithms on what data.

We have gone through the previous post, Introduction to machine learning.

Machine learning is used to filter spam data, recognizing the face, recommendation engines.When you have a large data set on which you’d like to perform analytical analysis or for example to recognize the patterns.

To avoid explicit programming, we can use machine learning, to train computers which can learn, analyse and act on the data as we specified.These qualities make machine learning more powerful on these days and also all the machine learning softwares are free.We can also implement our application on single machine or massive scale.

We can use machine learning libraries in all languages, environment you prefer (java, c++, python...etc languages, windows, linux...Etc OSs)

Here I am giving brief introduction of 11 machine learning tools, provides functionality for individual apps.

Tuesday, 8 November 2016

Difference between supervised, unsupervised Machine learning

Difference between supervised, unsupervised Machine learning:

As we studied about the introduction of Machine learning in the previous post, I am just refreshing again in two lines below.

Machine learning is a field of computer science, probability theory, and optimization theory; this allows the people complex tasks to be solved for which a logical/procedural approach would not be possible or feasible.

The different categories of machine learning are shown below
  • Supervised learning
  • Unsupervised learning

Supervised learning:

In supervised learning, we have some really complex function from inputs to outputs. we have lots of examples of input/output pairs, but we don't know what that complicated function is. Using supervised learning algorithm we can make it possible.

Monday, 7 November 2016

Introduction to machine learning

Introduction to machine learning:

What is Machine Learning?

Now a days Machine learning is the more weighted and costly topic to learn. In this post I would like to share my knowledge on machine learning. Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed.

The main target of Machine learning is the development of computer programs that can teach themselves to grow and change when exposed to new data.

The machine learning process is very similar to data mining.The data mining process is also searches through the data which looks for the patterns. Similarly machine learning uses the data to detect the patterns and adjust the programs accordingly.