Take advantage of a full-fledged code editor the same way as in your local machine.

Google Colab and VS Code are the most popular editor tools used by many Python developers and Researchers to develop different tech solutions or systems (especially in Machine Learning & Data Science).

Many Python developers and Data scientists know how to use Google Colab, but do you know that you can set up a VS Code on Google Colab and use it as an editor the same way as in your local machine?

In this article, you will learn

  1. How to install the colabcode python package.
  2. How to start the VS Code (code server).
  3. How to access the online VS…


In python, a String is a sequence of characters that may contain special characters or alphanumeric characters, for example, “we meet on Friday at 08:00 am”. It is possible to access sub-parts of the string commonly known as a python substring.

You can also define substring as a sequence of characters within a string. From the previous example, python substrings can be “Friday”, “at”, “meet”, and others.

Python provides different ways and methods to generate a substring, check if a substring is present, index of a substring, and more.

You can extract a substring from a string by slicing with…


Learn the distinctions between Artificial Intelligence and Machine Learning

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Today, artificial intelligence and machine learning are two popular terms that have been often used interchangeably to describe an intelligent software or system. Even though both AI and ML are based on statistics and mathematics, they are not the same thing.

Many people have been confused by these two terms. In this article, you will learn the distinctions between AI and ML with vivid examples.

What is AI (Artificial Intelligence)?

Artificial intelligence, or AI, is the ability of a computer or machine to mimic or imitate human intelligent behavior and perform human-like tasks.

Artificial intelligence performs tasks that require human intelligence such as thinking, reasoning…


A simple way to deploy your NLP Model

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This is the second and final part of the series on How to build and deploy an NLP model with FastAPI. In the first part, we looked at how to build an NLP model that can classify movie reviews into different sentiments.

In this second and final part, you will learn

  • What is FastAPI and how to install it.
  • How to deploy your model with FastAPI.
  • How to use your deployed NLP model in any Python application.

So let’s get started.🚀

What is FastAPI?

FastAPI is the fast and modern python web framework for building different APIs. …


A simple way to deploy your NLP Model.

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Model deployment is one of the most important skills you should have if you’re going to work with NLP models.

Model deployment is the process of integrating your model into an existing production environment. The model will receive input and predict an output for decision-making for a specific use case.

“Only when a model is fully integrated with the business systems, we can extract real value from its predictions”. — Christopher Samiullah

There are different ways you can deploy your NLP model into production, you can use Flask, Django, Bottle e.t.c.But …


Good African language datasets for numerous NLP tasks.

Image source by pangea.global

Africa has over 2000 languages however, these languages are not well represented in the existing Natural language processing (NLP) ecosystem. One of the challenges is the lack of useful African language datasets that can be used to solve different social and economical problems.

In this article, I have compiled a list of African language datasets from across the web. These datasets can be used in numerous NLP tasks such as text classification, named entity recognition, machine translation, sentiment analysis, speech recognition, and topic modeling.

This collection of datasets have been made public to give you an opportunity to use your…


Scikit-learn remains one of the most popular open-source and free machine learning libraries for Python. The scikit-learn library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction.

Many data scientists, machine learning engineers, and researchers rely on this library for their machine learning projects. I personally love using the scikit-learn library because it offers a ton of flexibility and it’s easy to understand its documentation with a lot of examples.

In this article, I’m happy to share with you the 5 best new features in scikit-learn 0.24.

Install the Latest Version of the Scikit-Learn Library

Firstly, make sure…


A simple trick to Improve Model Performance.

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When you training a machine learning model, you can have some features in your dataset that represent categorical values. Categorical features are types of data that may be divided into groups.

There are three common categorical data types which are:

  1. Ordinal — This has a set of orders. Example: rating happiness on a scale of 1–10
  2. Binary — This has only two values. Example: Male or Female
  3. Nominal — This does not have any set of orders. Example: Countries

Most machine learning algorithms require numerical input and output variables. Therefore you will have to transform categorical features in your dataset…


They say data is the new oil, but we don’t use the oil directly from its source. It has to be processed and cleaned before we use it for different purposes.
The same applies to data, we don’t use it directly from its source. It also has to be processed.


The first virtual hackathon for East Africa countries.

A few weeks ago, I and fellow Zindi ambassadors from East Africa organized the first East African virtual machine learning hackathon called AI4D Swahili News Classification Challenge. The virtual hackathon was a private hackathon open to participants from East Africa Countries (Tanzania, Kenya, Malawi, Uganda, and Rwanda).

If you don’t know Zindi, it is Africa’s largest data science competition platform, solving complex challenges using artificial intelligence (AI) and machine learning (ML). …

Davis David

Data Scientist | AI Practitioner | Software Developer. Giving talks, teaching, writing. Contact me to collaborate davisdavid179@gmail.com

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