Introduction to Data Analysis with PYTHON  Pandas

Easycoding

Introduction to machine learning with python for beginners

<h2>Introduction to Data Science and Machine Learning for intermediate beginner level. </h2><h2>Prerequisites: </h2><h3>Basic Python or any other programming background</h3><h3>Linear algebra </h3><h2></h2><h2>Course Description:</h2><p>This course is comprised of four lessons, two hours each. It will give you a basic understanding of how to use pandas for data analysis and how to implement linear regression and classification algorithms.  We will be scratching the surface only. In order to get the most out of this course, we recommend completing the FREE course on pandas and ML on Kaggle ( link is provided at the end of the page).  </p><p>Introduction to following core machine learning libraries :  </p><h3>Numpy, Pandas, Matplotlib, Seaborn, ScikitLearn</h3><h2>Lesson 1: Introduction to Data Analysis with Pandas </h2><ul><li>Pandas Series and DataFrames</li><li>indexing and slice Pandas DataFrames columns</li><li>Manipulating columns </li><li>Using .loc[] and .iloc[]</li><li>Dropping rows and columns</li><li>Using Groupby and aggregate functions</li><li>Using .apply functions</li></ul><h2>Lesson 2: Data  preparation and Visualization with Pandas </h2><ul><li>Dealing with duplicate data</li><li>Dealing with missing values</li><li>Dealing with categorical data</li><li>Dealing with text data</li><li>Data Visualization</li></ul><h2>Lesson 3:Introduction to Machine Learning  Part 1 (Implementation of Linear regression algorithm)</h2><p>		United States House price prediction using linear regress</p><ul><li>Understanding Data</li><li>Building Model</li><li>Evaluation Criteria </li></ul><h2>Lesson 4: Introduction to  Machine Learning Part 2 (Implementation of Classification algorithm)  </h2><ul><li>Exploratory Data analysis of  Iris dataset</li><li>Correlation and Basic stats</li><li>Data Visualization</li><li>Implementation of KNN classifier</li></ul><p><strong>Notes:</strong></p><p><strong>Upon successful completion, you will get an attendance certificate.</strong></p><p><strong>For  Completing you must submit your project (on our chosen dataset)  to your GitHub account. </strong></p><p><strong>Attend all lessons. </strong></p><p>Please go through the following notebook to familiarise yourself  with the process</p><p>https://www.kaggle.com/dansbecker/your-first-machine-learning-model</p><p>We look forward to welcoming you.</p>

<p>In order to confirm your booking, please follow Flourishing Life ai's  <a href="https://www.linkedin.com/company/flourishing-lifeai/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">LINKEDIN</a>  page.</p><p>We share stories about the latest machine learning technologies, applications and use cases, job information, conferences, research funding, and PhD funding opportunities.  </p>

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

Introduction to Data Analysis with PYTHON Pandas

More events from Easycoding

Discover more events from Easycoding, from Science & Tech to other experiences you might love.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.

Introduction to Data Analysis with PYTHON Pandas

More events from Easycoding

Discover more events from Easycoding, from Science & Tech to other experiences you might love.

You might also like...

Browse more events with different dates, prices, and formats to find your next great experience.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.