Beginner’s Guide To Machine Learning

Machine learning is a field of artificial intelligence. And it allows any AI system to automatically develop algorithms when uncovered a new data or on the basis of similar data on the past. The humans have best learning abilities, our actions, patterns of neural network and development since the beginning of the human kind are responsible for learning abilities. The big companies have already adopted the technology and continue working for updates. The possibilities are elaborating to increase the use of machine learning for protection, prediction, faulty algorithm detection, users interest and many other by companies.    

At Google, I/O 2017 Google announces a new TensorFlow lite. This TensorFlow Lite allow a mobile-optimized version of its machine learning algorithms. Tensor flow is open source library for machine learning (developed by Google).

Facebook use Machine Learning to analyze user’s news feed. That’s helpful to suggest related posts and related ads.   

Microsoft’s Azure machine learning is available for developers. Microsoft uses machine learning in Bing, Office, Xbox games and others.

Beginner’s guide to machine learning

Planning is important before starting anything. In a case of the long-term learning process, it is must. Probably this post helps you to plan Machine learning in proper sequence.

1.Read Books

Reading is important because it enables and develops the mind. A good book can reduce your efforts. There of two choices of book selection first for beginners and another is for practical purpose. Although beginners can select a proper machine learning based on personal interest on basis of types of machine learning field. is making a list of Machine learning books for beginners and for practical purpose.

2.Take an online course

You can choose an online course to understand Machine learning properly. By taking an online course, you can access notes, assignments, discussion, take quizzes for practice, and available most of the time. Online courses can help you to build and improve your working skills properly. The problem with getting online is the one disadvantage of online course.

3.Select a language

There are many purposes of learning machine learning either for a job purpose or research and development purpose. The most asked question from beginners is what or which programming language is best for machine learning?  The choice of machine learning can be depending upon areas of AI. R and Python programming languages are suggested for data analysis. MATLAB (use vectors and matrices concepts) is the perfect choice for researchers and students. Python is mostly suggested for beginners. You can also select C++, C, Java and other languages for Machine learning.

4.Select an area

Modern machine learning applications helping company to increase overall income and work efficiently. After getting sufficient knowledge in the programming field. You can select an Area based on personal interest. There are many new areas has been introduced because of research objectives. Here is a list of few you can pick one area to be an expert on it.    

  • Deep learning –                            for personal use, research, development of GPUs
  • Artificial neural networks –       development of structures like neurons (artificially)
  • Decision tree learning –               for predictive model
  • Genetic algorithms –                     for researchers and genotype solution
  • Rule-based machine learning – many uses
  • Support vector machines –          for classification and regression.

See more: 3 Most Challenging AI Sub-Fields

5.Career options in machine learning

A job is the ultimate goals of many of the peoples. machine learning algorithms can be used for many purposes. Prediction, data cleaning, fraud analytics. Data Science is currently used in many organizations. And mathematics, statistics, programming and communication skills are the basic requirements for Machine Learning jobs. No matter what area you select professionalism is important.


Beginning the age of AI is impossible without machine learning. We are asking to our readers what things makes a good programmer in machine learning. 


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