Artificial Intelligence (AI), Machine Learning (ML), Deep Learning and Big data as a career

Artificial Intelligence (AI), Machine Learning, Deep Learning and Big data

Even though computers can do things faster than humans they lack intelligence, ability to think and self-learning.  Machine Learning is a branch of computer science that is seriously focusing on techniques that gives self-learning ability to computers.

You might have many puzzling questions like, what is machine learning, what is the best machine learning tutorial, how to learn machine learning, what is the best machine learning course, machine learning vs artificial intelligence, machine learning certification course, machine learning framework, machine learning programming tools and languages etc.,  In this article you find answers to all if these questions.

Various machine learning algorithms have been developed for many machine learning applications.
For example, a computer machine learning algorithm can count vehicles at a traffic signal. Understand the voice of a person etc., Google uses machine learning to learn trends around the world.

Big data, data science or data sciences, deep learning, machine learning, artificial intelligence or AI are the terminologies that confuses us when we start thinking about this topic. I would like to explain these in short for clarity.

Big data: 
Big data is a technology that has set of algorithms that deals with large data sets both structured (example: databases) and unstructured (example: files).  Learning from data is the key here. It focuses on learning patterns, trends and its relationship with humans etc.,
For example: Facebook and twitter uses big data techniques to analyze the trends and emotions from their volume of posts and tweets.

Deep Learning: 
Deep learning is a spin of machine learning techniques which is based on learning data representations. It is primarily focused to achieve one of the main goal of machine learning which is artificial intelligence. It can be a supervised learning, partially supervised or unsupervised learning.

Artificial intelligence or AI : 
AI is basically focused to give intelligence to machines in order to take decisions based on things that it perceives through its sensors or data to achieve a specific goal. For example, Natural language processing is one such ability of computers.

Machine learning vs Artificial Intelligence vs Deep learning: 
AI is broader concept, which focuses on giving ability to machines to perform independent tasks like humans. Machine learning (ML) is a sub-discipline of AI which is more narrowed down and a step further where we give some data to computers and ask it to learn on its own with the help of ML algorithms. ML techniques use neural networks (like humans) to mimic the way humans think to take a decision or to solve a problem.
Deep Learning uses narrowed down sets of ML. It uses subset of ML techniques to bring the ability to solve any problem by using human like thoughts.
Example: Google uses ML techniques to process human voice (voice to text and text to voice).

Machine Learning tools:
Many open source machine learning tools are available for free. Some of the famous tools are: R, Python, CNTK, DeepLearning4j, GNU Octave, H2O, Torch, TensorFlow, OpenAI Gym, mlpy, MLPACK etc.,

Following are few interesting Machine learning applications:
Machine learning approach in financial markets
Machine learning approach to android malware detection
Machine learning approach in twitter user classification
Machine learning approach for product matching and categorization
ML approach for efficient traffic classification
ML approach for non-blind image deconvolution
Machine Learning approach to routing
Machine Learning approach to live migration modeling

Machine Learning Certification Course: 
Coursera machine learning certifications, one of the best programs. They offer online machine learning courses.
Python machine learning courses like R, mlpy etc., can be self-learned with the help of internet.
www.datacamp.comoffers a free R learning course. You can download R machine learning packages from github.

Once you learn these courses and have a certification it is easy to fetch machine learning jobs.

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