Health Technology Enthusiast || Medical Rehabilitation Undergrad || Aspiring Dermatologist || Data scientist and Machine Learning Enthusiast
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Picture from MessageOps

There’s this desire you get to share your work with others after building an application as you wouldn’t be able to carry your laptop to show people one after the other how great what you built is. Heroku shows its face where it matters, allowing developers to get on with what they do, in order to make them focus on building great apps which is the most important.

Heroku is a container-based cloud Platform as a Service (PaaS) mainly for deploying, managing, and scaling modern apps. With Heroku, there is no need to learn about server configuration, network management, or tuning the latest version of a database as all you have to do is to sign-up, download some needed tools, push your codes to the platform effortlessly, and get it up and running. …


How we won first place at the IdeaLabAi Hackathon hosted by the Sahara Ventures and the Tanzania AI Lab

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image by SpringerLink

Cancer of all types is increasing exponentially in the countries and regions at large. Cervical cancer, which is caused by a certain strain of the Human Papillomavirus (HPV), presents a significant public health threat to women on the African continent. All but one of the top 20 countries worldwide with the highest burden of Cervical cancer in 2018 were in Africa in which Tanzania was among.

In Tanzania, cancer control activities and services are undertaken by a wide range of government and non-government agencies, most of which have been done by ORCI and to a lesser extent by some other NGOs. …


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Photo by Caspar Camille Rubin on Unsplash

One of the biggest hurdles of democratizing Deep Learning has been the need for a GPU accelerated environment. If we want to spend our time efficiently testing and learning across problem statements we need a GPU-based server. But these GPU based environments across platforms like GCP, AWS, Azure, Paper-space can amount to a huge cost. This cost when combined with the cost of storage and if we are using instances that are persistent may really add to the burden on our money bag.

But some amazing news came in when Kaggle and Google Colab introduced GPU-enabled kernels which can be now used to decipher and solve deep learning problems across the problem statements without the need to buy a GPU. …


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picture by reddit.com

What if Data Science, most time called the sexiest job in the twenty-first century encompasses talents without skills?

What if everybody learned the basics of Data Science without extracting values and motivations that come from community engagements, that creates a drive for talents to aspire and yearn more?

Now imagine what would’ve become of Nigerians Developers without this superlative, top-notch community whose interest, visions, and objectives don’t depend on maximizing profit alone but to raise faculties, strong points, talents, and potentials in Nigeria, exerting them through in-house, and inter-university competitions, pieces of training, internships, and scholarships.

Sure, I can see you’re in haste to know how I’ve been impacted! …


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Photo by Serena Repice Lentini on Unsplash

What would you have done as a developer, who has just learned the fundamentals of Python while navigating between the most used Python Application Programming Interface Sublime Text and Python/Anaconda Command Prompt in running and executing your codes, to interactively develop and present sophisticated Data Science projects without Jupyter Notebook?

Jupyter notebook is an incredibly powerful web application tool that allows you to integrates code and its output into a single document containing a succession of steps like narrative text input, data collection, cleaning, transformation, numerical simulation, statistical modeling, and many more.

More so, it’s a single document where you can run code, display the output, also add explanations, formulas, charts, and make your work more transparent, understandable, repeatable, and shareable. …


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Photo by Serena Repice Lentini on Unsplash

What would you have done as a developer, who has just learnt the fundamentals of Python while navigating between the most used Python Application Programming Interface Sublime Text and Python/Anaconda Command Prompt in running and executing your codes, to interactively develop and present sophisticated Data Science projects without Jupyter Notebook?

Jupyter notebook is an incredibly powerful web application tool that allows you to integrates code and its output into a single document containing a succession of steps like narrative text input, data collection, cleaning, transformation, numerical simulation, statistical modeling, and many more.

More so, it’s a single document where you can run code, display the output, also add explanations, formulas, charts, and make your work more transparent, understandable, repeatable, and shareable. …


Understanding the most natural and pragmatic approach. Once you get a hang of it, implement real-world problems by delving deeper into Python programming.

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Most times, your coding sequence of steps have been perambulating around data analysis, preprocessing, visualization, modeling, all these are part of thinking routinely.

To understand the intuitions behind this, let’s take, for example, the Nigeria’s system of education. We have a sequence of pre-primary>>primary>>secondary>> tertiary. This sequential viewpoint works if we are talking about maybe Nigeria as a country alone. However, if this is about continents and regions, you’d have to think about thousands of countries' educational systems all over the world. …


Remarkably, it costs an arm and a leg to get a decent GPU from existing cloud providers. So, how do we build a Machine and Deep Learning Models without burning a hole in our pockets? How do we stop the usual “memory error” messages that do pop up any time we execute algorithms on a large dataset? You are having an ancient PC with a very low computational power?

Relax. There’s Google Colab!.

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from dreamstime.com

What's Google Colab?

It’s a tremendous online browser-based Jupyter Notebook that allows us to train Machine and Deep Learning models on CPUs, GPUs, TPUs for free!

Sounds too good to be true, but thanks to Google, we can now operate on large datasets, build complex models, and even share our work seamlessly with others. That’s the power of Google Colab. …


Machine Learning algorithms in predicting which customers will default on their loans based on their financial information and historical data

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Image from Medical Tourism Corporation

Loan lending has been an important part of daily lives for organizations and individuals alike. With the ever-increasing competition in the financial world and due to a significant amount of financial constraints, the activity of taking a loan has become more or less inevitable. Individuals around the world depend on the activity of loan lending for reasons such as overcoming their financial constraints in order for them to achieve some personal goals. …


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The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet.

Using this model, BigMart will try to understand the properties of products and outlets which play a key role in increasing sales.

This article will acquaint you on everything you need to know in order to engage in hackathons/ competitions. It will take you through;

  • Data Loading
  • Data preprocessing
  • Feature engineering
  • Building a…

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