The process of developing a machine learning model can be many things: from a rewarding learning experience, to a dreadful and frustrating process of low accuracy and debugging nightmares. One aspect of the machine learning workflow that used to be tricky is the prototyping phase, a stage where we want to have a simple interface to showcase our model’s capabilities.
Streamlit, a framework for writing data apps, came to fill in that gap by providing people with the ability to give life to their AI models as quickly as possible, without the painful overhead of writing a full-fledged GUI.
With the recent release of the very much anticipated beta version of the Notion API, a lot of integrations between apps are now possible, and an entire universe of possibilities is now open for data science projects.
In this post, I will show you how to build a simple project tracking dashboard with Streamlit and the Notion API.
Let’s start with creating a page on Notion. Now, you need to create an integration token on your Notion page and then share your database with that integration. A detailed tutorial on how to do that can be found here.
Developing a skill is much easier if we are able to streamline the process of practicing it. For me, improving my data science skills involves weekly and sometimes daily practice of the different aspects of doing data science work: data collection, data cleaning and preprocessing, data visualization, modelling and more.
In this post, I will share my basic template for practicing data science with a practical example.
One good way to simplify the cycle of practicing your data science skills is to clarify what are the steps that take you from data to insight. …
When you first get to your laptop/desktop in the morning you probably open quite a few applications. Doing this every day can get tiresome, so I wrote a script to automate the process of starting my day on my desktop, and in this tutorial I will show you how it works.
This script streamlines my daily routine right after booting my computer in the morning, handling a lot of the the basic manual tasks I have to get through before I can actually start working.
This routine involves processes like opening specific browser tabs, showing routine reminders, starting tracking scripts…
I am periodically looking to improve my pipeline of knowledge management, and, upon testing multiple systems for note taking, I realized the underappreciated value of tags for notes. So, in this post I will be sharing my tagging system to optimize your notes.
Tags are like micro bridges that allow you to give your overall knowledge storage a language to communicate high level organizational aspects of your notes.
For me, tags can…
Reviewing is crucial, as humans we were not build to look at a piece of information only once. Our brain is like a muscle and as any muscle, it has to be used to improve, so we should periodically review information, tasks and current strategies to be consistently evolving in our daily routines.
In this article, I will describe a simple system for reviewing your notes, tasks and workflow strategies to make sure you are always on top of your productivity game.
Let’s start with the simplest tip: you should periodically (weekly) review…
Attention seems to be a commodity these days. Every app and website you visit want some piece of your attention, it is almost a currency. Therefore, it makes sense to have as much control as we possibly can over our own focused attention.
Today, I will show you how to track and visualize your focused time using Python and Streamlit
The steps will be:
Let’s begin by writing the script to track your focus:
Let’s unpack what is happening here:
Your workflow is the combination of all of the projects you undertake through out the day, week or month — from your habits to your work assignments and learning ventures.
I tend to think that everything we do should be integrated in some way that gives us a feeling of connectedness with our own routine. It is possible to join projects, learning ventures as well as work tasks, as part of a bigger and more integrated process that constitutes our workflow.
So, in this article, I will show you how to organize a cycle that integrates work, personal projects…
Writing Python scripts to solve a wide range of small-scale problems is one of my daily pleasures. I always enjoy figuring out that Pythonic answer to a problem, and also love when I don’t know the solution but can quickly look that up on stack overflow and discover that some wonderful soul on the internet has already solved it for my accidental delight.
In this article, I will share 9 Python scripts that solve practical problems — problems that you will probably encounter on your Pythonic explorations.
from collections import defaultdict
import numpy as npq = defaultdict(lambda: np.zeros(5))#…
Measuring progress is a trademark of improvement. I challenge you to find one world class athlete today that does not have some kind of metric to define her or his progress in whatever sport they are in.
With intellectual work is no different, we need good approaches to track ourselves however, what benefits can we get from self-tracking? What kind of metrics should we track?
In this post I will share a general outline of my approach to self-tracking and how it can be a helpful tool for providing insight on productivity.
Machine Learning Engineer. I write about AI | Data Science | Productivity & Learning.