Author: Pratik

Machine Learning Bootcamp – Introduction and Hands-on @ RV College of Engineering, Bangalore

We have a one-day workshop on Introduction to Machine Learning with Drupal Bangalore. In this workshop, you will learn how to apply various Machine Learning techniques for everyday business problems.

  • Date: Saturday, Dec 16, 2017
  • Place: R. V. College of Engineering, Bangalore
  • Time: 11.30 am – 1.30 pm: Presentation and Demo, 2.30 pm – 4.30 pm: Hands-on

What will be covered?

An exposure to Machine Learning using Python to analyze, draw intelligence and build powerful models using real-world datasets. You’ll also gain the insights to apply data processing and Machine Learning techniques in real time.

After completing this workshop, you will be able to build and optimize your own automated classifier to extract insights from real-world data sets.

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NumPy and Pandas Tutorial – Data Analysis with Python

Python is increasingly being used as a scientific language. Matrix and vector manipulations are extremely important for scientific computations. Both NumPy and Pandas have emerged to be essential libraries for any scientific computation, including machine learning, in python due to their intuitive syntax and high-performance matrix computation capabilities.

In this post, we will provide an overview of the common functionalities of NumPy and Pandas. We will realize the similarity of these libraries with existing toolboxes in R and MATLAB. This similarity and added flexibility have resulted in wide acceptance of python in the scientific community lately. Topic covered in the blog are:

  1. Overview of NumPy
  2. Overview of Pandas
  3. Using Matplotlib

This post is an excerpt from a live hands-on training conducted by CloudxLab on 25th Nov 2017. It was attended by more than 100 learners around the globe. The participants were from countries namely; United States, Canada, Australia, Indonesia, India, Thailand, Philippines, Malaysia, Macao, Japan, Hong Kong, Singapore, United Kingdom, Saudi Arabia, Nepal, & New Zealand.

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