How to use Dask with TQDM library?

How to use Dask with TQDM library?

How to use Dask with TQDM library?

This recipe helps you use Dask with TQDM library


Recipe Objective

How to use Dask with TQDM library.

TQDM is a package that is used for iterations. TQDM shows the progress bar while implementing it with Dask. They both together can do iteration process more easily and makes it less frustrating when dealt with bigger datasets.

Step 1- Importing Libraries

from dask import delayed,compute from tqdm import trange from time import sleep

Step 2- Using Dask and TQDM together.

From Dask we are using delayed and compute function with trange function from tqdm.

list= [] x=10 for i in trange(x): list.append(delayed(x)(i)) print(compute(list))

Relevant Projects

Choosing the right Time Series Forecasting Methods
There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.

Data Science Project on Wine Quality Prediction in R
In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.

Machine Learning Project to Forecast Rossmann Store Sales
In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.

Perform Time series modelling using Facebook Prophet
In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.

Expedia Hotel Recommendations Data Science Project
In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.

NLP and Deep Learning For Fake News Classification in Python
In this project you will use Python to implement various machine learning methods( RNN, LSTM, GRU) for fake news classification.

Walmart Sales Forecasting Data Science Project
Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.

Deep Learning with Keras in R to Predict Customer Churn
In this deep learning project, we will predict customer churn using Artificial Neural Networks and learn how to model an ANN in R with the keras deep learning package.

Topic modelling using Kmeans clustering to group customer reviews
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.

Loan Eligibility Prediction using Gradient Boosting Classifier
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.