What is the correct order to learn concepts in Python for machine learning?

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I am new to domain I wanna know what is the correct order to learn concepts in Python for machine learning?

I do have some generic programming knowledge using C and Java.
Jul 25, 2018 in Python by Anmol
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Machine Learning is a vast domain. It requires a mixture of multidisciplinary skills ranging from an intersection of mathematics, statistics, computer science, communication, and business.

Now, Machine Learning using Python is one of the best combinations to worry about.

Being a Data Science professional, I can recommend the best available courses:

Here is a list, you can follow to pursue your goal:

  1. Learn Python Python Programming: It will help you gain expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will learn to use libraries like Pandas, Numpy, Matplotlib, Scipy, Scikit, Pyspark and master the concepts like Python machine learning, scripts, sequence, web scraping and big data analytics leveraging Apache Spark. Below is the course, you can go for mastering python: Python Certification Course | Python Training | Edureka
  2. Data Science with Python: This Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. It exposes you to concepts of Statistics, Time Series and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. Throughout the Data Science Certification Course you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR: Edureka
answered Jul 25, 2018 by ANMOL
• 3,620 points

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