Data Science- Python for Machine Learning

Hands on Python for Data Science

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Last Updated: 2022-04-25 06:04:33 English Course Type: Self Learning

Work on data science projects using Python.
Python Basics
Data Mining
Data Cleaning

How to use this course:

This class is not meant to be merely observed, it is a practical lesson which requires you to open your Jupyter notebook and type the code as you see it on the screen. This way you will understand how the code works. Feel free to experiment with the code by entering your own values.

A hands-on approach to learning Data Science using Jupyter Notebooks. All explanations are present on the screen so that you can pause the video and read them at your own pace. Installation instructions have been provided for Python as well as it's libraries.

Installation instructions have been provided in the course for the following libraries:
Jupyter Notebooks
Python
Numpy
Scipy
Matplotlib
Pandas
Scikit-Learn
Seaborn

Beginners

Section 1 : Introduction to Jupyter Notebooks 2 Lectures 00:11:36
Lecture 1 :
Tour of Jupyter Notebooks Preview
Lecture 2 :
Jupyter Notebooks Quiz
A quick quiz to test students.
Section 2 : Python Basics 3 Lectures 00:34:06
Lecture 1 :
Python Basics - Part 1
Links to Python installation instructions have been provided for Mac, Windows and Linux. We begin with the basics of Python such as: Data types - A detailed explanation of all the data types available in Python Declaring Variables and Assigning Values - How to declare a variable and then assign a value to it. Printing Values- After declaring and assigning values to a variable, it must be printed in order to be visible. Importing Libraries - How to import Python Libraries so that they can be used in the notebook. 5. Python Operators - How to conduct basic mathematical operations such as: â€¢ Additionâ€¢ Subtractionâ€¢ Multiplication â€¢ Division â€¢ Comparison (greater than, less than or equal to) â€¢ Logical operators (and, or , not, xor) â€¢ Bitwise operators â€¢ Assignment operators â€¢ Identity operators â€¢ Membership operators. 6. Strings â€¢ Find the length of a string â€¢ Replace a word â€¢ Find a word 7. Lists â€¢ Add an element to a list â€¢ Print a section of a list â€¢ Remove an element of a list 8. Tuples9. Dictionaries â€¢ Creating a dictionary â€¢ Print an element â€¢ Delete an element
Lecture 2 :
Python Basics - Part 2
Continuation of Python basics: 1. Control Flow 2. Loops â€¢ For loopâ€¢ While loopâ€¢ Nested loopâ€¢ Adding a Breakâ€¢ Continuing a loop 3. Syntax 4. Functions â€¢ Built in functionsâ€¢ User defined functions
Lecture 3 :
Python Basics - Part 3
The final part of the series 'Python Basics' : Classes Objects Modules Exception Handling
Section 3 : Basic Python Libraries for Data Science 1 Lectures
Lecture 1 :
Installation instructions for Numpy, Scipy, Matplotlib, Pandas and Scikit-Learn
Select the appropriate link below for your system and install all the necessary libraries for the remainder of this course.
Section 4 : Numpy 1 Lectures 00:10:39
Lecture 1 :
Numpy
Section 5 : Scipy 1 Lectures 00:09:38
Lecture 1 :
Scipy
Section 6 : Matplotlib 1 Lectures 00:11:00
Lecture 1 :
Matplotlib
Section 7 : Pandas 1 Lectures 00:13:26
Lecture 1 :
Pandas
Section 8 : Machine Learning Concepts 1 Lectures 00:10:42
Lecture 1 :
Machine Learning Basics
Section 9 : Scikit-learn 1 Lectures 00:09:20
Lecture 1 :
Scikit-learn

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Vinita Silaparasetty,

35288 Course Views

1 Courses

Vinita Silaparasetty is currently exploring the field of Artificial Intelligence, particularly in Machine Learning, Deep Learning and Neural Networks. 1) Quora Top writer (2018) 2) Co-organizer of the "Bangalore Artificial Intelligence Meetup" group 3) Co-organizer of the "AI for Women" meetup group 4) Ambassador for the "Charter of Compassion" #datascience #artificialintelligence #machinelearning #vinitas #vinita #vinitamohan #deeplearning