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 …
3 Exploratory Data Analysis Tools In Python For Data Science Read More »
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) …
Text Classification with Flair – Pytorch NLP Framework Read More »
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 …
How to Split Dataset into Training and Testing Dataset For Machine Learning Read More »
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 …
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 …
Exploratory Data Analysis of Drug Review Dataset using Python Read More »
In this series of tutorials and blog posts we will be exploring Natural Language Processing(NLP for short) – a branch of Machine Learning and Data Science. We will be taking short and exciting tutorials on most of the concepts used in NLP and how it is applied in real life. We will take each concept …
Streamlit components have so much potential. With the introduction of the components system in streamlit, we can now build additional features and integrate into the web apps we have been building. You can check out the docs on the components here. In this tutorial we will explore one of the components – .html(). We will …
Building A Calculator with Streamlit Components and HTML Read More »
Unsupervised Machine learning has several applications among them include its usage in identifying patterns and for clustering similar data into clusters or groups. In this tutorial we will see how to use unsupervised ML to perform a simple task of identifying the right continents a country belongs to given the longitude and the latitude. Unsupervised …
Clustering Countries into Continents using Unsupervised Machine Learning Read More »
In this tutorial we will build a simple natural language processing(NLP) app with an awesome package called Spacy-Streamlit. Spacy-Streamlit is a python package that is useful for visualizing spaCy models and building interactive spaCy-powered apps with Streamlit. It has several functions and utils for visualizing spacy’s essential NLP features such as Tokenization using visualize_tokens() NER(Named …
In this fourth industrial age – the Age of AI, the knowledge and applications of machine learning is essential for every business and industry. It has a lot of potential and benefit when incorporated into your business . But not everyone has the time and the energy to learn the intricacies of Data Science and …