How Should You Learn Python For Machine Learning And Artificial Intelligence?

February 14, 2019
Big data and machine learning


In this era of technology when you always have an assistant, be it SIRI or Google Assistant or some other with you to help you out with the working of the day, it is no secret that Artificial Intelligence and Machine learning are significant. Python is one of the most popular programming languages used for writing codes for the mentioned two. MNCs are regularly hiring people who have done Python certification courses. Among the numerous big data and machine learning courses, Python certification courses are the most valued ones. That is why in this piece of writing we will be discussing the proper steps for you to learn Python for writing Machine Learning and Artificial Intelligence programs.

  • Master basic Python skills: If you want to use Python in artificial intelligence programs like professionals, then you should first focus on learning the basics of Python. Amongst the number of Python certification courses available on the internet, the one offered by Imarticus Learning is best suited for the beginners as well as for pros.
  • Build the foundation of Machine Learning: After mastering the basics, you should be able to perform the act on the stage too. So, the next step is to lay the groundwork of basic Machine Learning. While studying Machine Learning, you are sure to come across problems requiring the knowledge of Python. So you shall learn how to use the learned Python basics in Machine Learning programs.
  • Take a look over the scientific Python packages: After the previous two steps, it is clear that you are well equipped in using in basic Python in writing codes of artificial intelligence and machine learning. So now let us move on a higher level. Apart from the primary Python language, there are many external function libraries usually employed in easing the processes of machine learning. These function libraries are also known as Scientific Python Libraries. Some of them have been enumerated below –
  1. Numpy: It is used for N-dimensional array objects.
  2. Pandas: It is one of the data analysis libraries which comprises structures like data-frames.
  3. Matplotlib: It is a plotting library capable of publishing 2-D plot which is of high quality.
  4. Scikit-learn: This is a type algorithm used for data analysis and data mining tasks.
  • Dive into machine learning topics which require Python: true in every aspect. After gaining the knowledge of necessary Python, Machine Learning, and Scientific Python libraries, now practice writing and working out numerous practical algorithms used in Machine learning by using Python. Try to solve the listed problems for a start –
    • K-means clustering
    • Decision trees
    • Linear regression
    • Logistic regression etc.
  • Dive deeper: After practicing the listed fundamental problems try to practice harder ones, to be able to become eligible in solving problems on a higher level. Try to formulate algorithms to solve multi-dimensional problems like –
    • Dimensionality Reduction
    • Vector machine etc.
  • Deep learning in Python: Mind you, this is an advanced topic to learn. At the same time, it is in high demand also. If you have followed all the listed steps properly then now you should try this one, i.e. Deep Learning.

Follow the points which are mentioned above, and you will find it easier to learn Python for machine learning. Python certification courses on Imarticus Learning follows the proper way to make a beginner, a master in writing codes in Python for machine learning. They also offer other big data and machine learning courses to enable you to widen your career prospects and attain all your professional goals.

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