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Pipreqs Tutorial – How to Create Requirements.txt File In Python with Ease

Reproducibility and re-usability of your Python projects is an essential aspect of being a software developer or engineer, and one of the ways to do so is to provide means that others can get the same working environments you used for your projects and the same versions of packages and libraries used. This is one …

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How to Create Requirements.txt File In Python

When working on any python project or data science project it is essential to always work in an environment that makes your project reusable and repeatable without any issues for anyone that picks up your project in the future. This will even help you yourself when you revisit your project in the future. One of …

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How to Add Layout to Streamlit Apps

Streamlit is awesome we several cool and useful features, in this tutorial we will explore yet another additional feature of streamlit – st.beta_columns() and st.beta_expander(). This feature is available from version 0.68 and upwards hence you will need to upgrade your previous version via pip install streamit -U or pip install streamlit –upgrade Let us …

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3 Exploratory Data Analysis Tools In Python For Data Science

Exploring your dataset is an essential aspect of every data science task or project. As an aspect of the Data Science Life Cycle , it allows you to derive descriptive and practical insight into what your data comprises of. It is essential to know how to derive such insight from your data by creating your …

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Text Classification with Flair – Pytorch NLP Framework

In today’s tutorial we will be exploring another powerful natural language processing library called Flair. We will be seeing how to use Flair for text classification. Specifically we will learn how to build a model to predict or classify text as either offensive or non-offensive. What is Flair? Flair is a state of the art(SOTA) …

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How to Split Dataset into Training and Testing Dataset For Machine Learning

One of the most important activities when building models is the ability to test and evaluate your model and have something to compare with that shows that your model actually worked. In order to do this you will need to have enough data to train and build a working model and also to test the …

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How to Run Streamlit Apps From Google’s Colab

The simplicity that streamlit offers for building apps is so cool and useful. But sometimes you may be constrained by lack of compute or incompatible  working environment on your local computer. In most cases Colab solves that problem. But what if you want to share your streamlit app with others from Colab. In this tutorial …

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Exploratory Data Analysis of Drug Review Dataset using Python

Exploratory Data Analysis is an important aspect of any data science project. It forms the initial steps before moving into the Machine learning aspects. In this tutorial we will be exploring the drug review dataset using python in an elaborate way.  In doing EDA (exploratory data analysis) it is recommended to keep in mind the …

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