Data Science and Machine Learning Tutorials
Such as NLP,ML,DL,AI and more
In the previous tutorial we saw how to deploy streamlit using docker. In this tutorial we will be looking at how to deploy our streamlit app to Google Cloud Platform App Engine using docker. Docker gives you the possibility to deploy apps on any available cloud platform such as GCP,Azure,AWS ,Alibabacloud etc. The main requirements …
How to Deploy Streamlit Apps to Google Cloud Platform(GCP App Engine) Read More »
In this tutorial we will be learning about how to customize your windows terminal with anaconda or any other program that runs in the command prompt. First of all we will install windows terminal and then anaconda. Installing Windows Terminal The requirements for installing windows terminal is that your Windows 10 Operating system must have …
How to Add Anaconda To Windows Terminal For Data Science Read More »
In a previous tutorial we learnt about the various ways of productionizing and deploying machine learning models and one of the ways is to use docker. In this tutorial we will be using docker to deploy our streamlit app. What is Docker? Docker is a platform for developers and sysadmins to build, share and run …
In a previous post, we learnt about the various ways we can productionize our machine learning models. In this tutorial we will be looking at how to serve our machine learning models as an API- which is one of the ways to productionize your ML model. There are several ways we can achieve this. We …
Serving Machine Learning Models as API with FastAPI Read More »
Building Machine learning models can be time consuming and tedious,but with the advent of Auto ML services and application we can reduce our burden . In this tutorial we will be building a Semi – Automated ML app with streamlit. It is going to be a drag and drop machine learning app that features Exploratory …
Building A Drag & Drop Machine Learning App with Streamlit Read More »
In this tutorial we will be looking at how to use the command line when working with a data science project. We will be doing data analysis with the command line – shell or bash. Most data science projects are done with languages such as Python,R,Julia, Javascript,Java ,C languages,Matlab . We will be checking how …
In this tutorial we will be building a document redaction app. Document redaction refers to the process of sanitizing and censoring a document based on selected terms. It is one of the applications of NLP – natural language processing. This image shows some of it use. In this case the important terms have been blacked …
Building A Document Redactor NLP App with Streamlit,Spacy and Python Read More »
In this tutorial we will be see how to render the named entities of a text extracted using spacy’s displacy in flask. First of all the basic requirement is to use the following packages Flask Spacy Flask-Markdown To install the various packages we will be using pip as below pip install flask Flask-Markdown spacy To …
How to Use Displacy in Flask For Named Entity Recognition Read More »
Artificial Intelligence which includes Machine learning,Deep Learning,etc has changed the world and it is going to continue to change our lives. As we begin to accumulate more data via the smart technologies we used, there is going to be a huge demand for storage of these data. But that is not all, there is also …
4 Ways to Productionize Your Machine Learning Models Read More »
In this tutorial , we will be learning how to deploy our awesome streamlit apps. The simplicity of streamlit makes it easier to build ML apps, Data Science Apps and other python apps. So what do you do if you want to deploy or publish your streamlit app? There are several options and platforms that …