How to build GLM models with Dask?
This recipe helps you build GLM models with Dask
Recipe Objective
How to build a GLM models with dask.
GLM models stands for Generalized Linear Models. It is mainly used to solve the regression problems containing continuous values.
The Dask-GLM project is nicely modulated, It allows different GLM families and Regularizers as well, It includes a relatively direct interface for implementing custom GLMs.
#! pip install dask_glm
Step 1- Importing Libraries
from dask_glm.datasets import make_regression
import dask_glm.algorithms
import dask
Step 2- Creating Regression model.
We will create the regression model and pass it through the persist to create the dataframe so that we get the partitions of 100 dask DataFrames.
x, y = make_regression(n_samples=2000, n_features=100, n_informative=5, chunksize=100)
x, y = dask.persist(x, y)
print(x)
print(y)
Step 3- Applying the algorithm function.
algo = dask_glm.algorithms.admm(X, y, max_iter=5)
algo
What Users are saying..
Ray han
Tech Leader | Stanford / Yale University
I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop... Read More
Relevant Projects
Machine Learning Projects
Data Science Projects
Python Projects for Data Science
Data Science Projects in R
Machine Learning Projects for Beginners
Deep Learning Projects
Neural Network Projects
Tensorflow Projects
NLP Projects
Kaggle Projects
IoT Projects
Big Data Projects
Hadoop Real-Time Projects Examples
Spark Projects
Data Analytics Projects for Students
You might also like
Data Science Tutorial
Data Scientist Salary
How to Become a Data Scientist
Data Analyst vs Data Scientist
Data Scientist Resume
Data Science Projects for Beginners
Machine Learning Engineer
Machine Learning Projects for Beginners
Datasets
Pandas Dataframe
Machine Learning Algorithms
Regression Analysis
MNIST Dataset
Data Science Interview Questions
Python Data Science Interview Questions
Spark Interview Questions
Hadoop Interview Questions
Data Analyst Interview Questions
Machine Learning Interview Questions
AWS vs Azure
Hadoop Architecture
Spark Architecture
Relevant Projects
Machine Learning project for Retail Price Optimization
In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.
Build a Similar Images Finder with Python, Keras, and Tensorflow
Build your own image similarity application using Python to search and find images of products that are similar to any given product. You will implement the K-Nearest Neighbor algorithm to find products with maximum similarity.
Loan Eligibility Prediction in Python using H2O.ai
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.
Learn to Build an End-to-End Machine Learning Pipeline - Part 1
In this Machine Learning Project, you will learn how to build an end-to-end machine learning pipeline for predicting truck delays, addressing a major challenge in the logistics industry.
MLOps AWS Project on Topic Modeling using Gunicorn Flask
In this project we will see the end-to-end machine learning development process to design, build and manage reproducible, testable, and evolvable machine learning models by using AWS
Hands-On Approach to Regression Discontinuity Design Python
In this machine learning project, you will learn to implement Regression Discontinuity Design Example in Python to determine the effect of age on Mortality Rate in Python.
Build a Customer Churn Prediction Model using Decision Trees
Develop a customer churn prediction model using decision tree machine learning algorithms and data science on streaming service data.
ML Model Deployment on AWS for Customer Churn Prediction
MLOps Project-Deploy Machine Learning Model to Production Python on AWS for Customer Churn Prediction
Build a Face Recognition System in Python using FaceNet
In this deep learning project, you will build your own face recognition system in Python using OpenCV and FaceNet by extracting features from an image of a person's face.
Build Regression Models in Python for House Price Prediction
In this Machine Learning Regression project, you will build and evaluate various regression models in Python for house price prediction.