Live PySpark for Data Science - V: ML Pipelines
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Live Session "PySpark for Data Science - V:
ML Piplines"

  • Unleash the Power of PySpark in this Live session.

By Selva Prabhakaran

  • English

  • November 19, Sunday - 10:30 AM IST | 22:00 PDT | 6:00 AM BST

What you will learn

01

PySpark linear
Regression

02

PySpark Ridge
Regression

03

PySpark Lasso
Regression

04

PySpark Logistic
Regression

05

PySpark Decision
Tree

06

PySpark Random
Forest

07

PySpark Gradient
Boost

08

PySpark K-Means
Clustering

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

About the course

You will learn the following skills by the end of the course:

  • LightGBM
  • XGBoost Random
  • Forest Decision Tree
  • Logistic Regression
  • Hyperparameter
  • Tuning Feature Importance Confusion Matrix
  • ROC AUC
  • Concordance and Discordance
  • Precision Recall Curve
  • Capture Rates and Gains
  • Feature Engineering
  • Label Encoding
  • Frequency Encoding
  • Chi-Square test ANOVA test
  • Exploratory Data Analysis
  • Memory
  • Optimization
  • Data Preprocessing

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

  • 4.8+Instructor rating

  • 200+ reviews

  • 50K+students

  • 33+ Courses

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