In this article, I generated an image dataset with Matplotlib, submitted it to Kaggle and trained a vanilla CNN model on Google Colab. My individual Computer Vision trip bundles together data-generating, preprocessing, modeling and evaluation steps.

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My own journey

I started my Computer Vision journey in a german Industrie, where one of my tasks is to take pictures for building an image dataset of machined parts’ surface. Later we built a model to classify and Individuate anomalies with Convolutional Neural Networks. It sounds cool, however, the work for collecting images using an industrial camera is not easy, in contrast always time-consuming.

Of course…

How to create a simple analog clock with Matplotlib package

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In this article, I will show you the process to build and design your analog clock using python package matplotlib.

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+. — Wikipedia

Online there are already many text and video tutorials to tell us how to create an analog or digital clock, typically with Qt, Tkinter which are usually used for GUI building. Another most famous package turtle is frequently introduced in python crash…

In this article, we focus on a naive Bayes classifier to check if somebody has covid-19 or not, and how severe is his infection, based on his symptoms. As the title revealed, the test prediction accuracy is not satisfying which fails to determine the severity of the infection with this method.

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1. Kaggle dataset

These data will help to identify whether any person is having a coronavirus disease or not based on some pre-defined standard symptoms. These symptoms are based on guidelines given by the World Health Organization (WHO) and the Ministry of Health and Family Welfare, India.

The dataset contains seven major…

In this article, our aim is to create an intuitive report with Matplotlib. Attention: during the work, none of the office software will be demanded. What we only use, is Python.

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A series of meaningful data plots works usually as ingredients in a report. As spoken, a good chart is better than a speech. If we have obtained these precious ingredients in advance, the last step is how to place them in a proper way.

Of course, we can use Microsoft Word, Powerpoint, etc. But not necessary. Here I present my recipe with Matplotlib.

1. Short introduction of data and charts

In this story, we demonstrate how we draw donut plots from complex excel sheets with python tools.

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As usual, our work starts with data, just like some people’s breakfast consists of donuts. There is no relationship between food and data, except that the donut chart has a doughnut-shaped figure.

Firstly, we have an excel file that records all sales information of an industry department from 2018 to 2020. The department established in 2018 has just experienced covid-19 year in China. Luckily, it has survived and celebrates the starting of the new year 2021.

Explanation of original data

Now we can look back on what happened to the department in the last three years. The excel composed of 3 sheets, contains the…

In this story, we can experience how to make use of all the delivery vouchers to monitor the warehouse inventory.

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In a supply chain, the warehousing function is very critical to link the material flows between the supplier and customer. Therewith, warehousing is actually part of a material management process concerned with the storage of materials to deliver on time. The warehouse can also be used to store the raw materials, some of the semi-finished goods and parts that are required for manufacturing, and the most important goods — finished goods which will be delivered to customers.

Last two months I was in a textile factory in China. Through talking with the owner of the factory, I have understood how…

This story is after an interview with a factory owner, with the help of Pandas to reveal the factory’s face hidden under data

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1. Background

Two months ago, I was in the biggest textile collecting and distributing center in Asia. The City has developed in recent few decades depending on its main industry — Textile. Therewith, I visited a small family factory in the suburbs. The owner of the factory has been managing this factory for more than 30 years. However, he has resisted recording everything that happened in the factory on paper. A modern computer has occurred in the factory just…

from the China textile City, Keqiao — the biggest textile collecting and distributing center in Asia

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The last two months I was in China, and visited a small factory in textile city Keqiao, to be exact, that is a sweatshop owned by a family. As the city was first built in the 1980s, this sweatshop is no more than 10 years younger than Keqiao.

The owner’s family has a long history with the textile industry, around 100 years. The grandfather of the interviewed factory owner had once also a small spinning workshop. Unfortunately, due to the Second World War, he…

Using Talos to grid search Hyperparameter in CNNs, e.g. a dog-cat CNN classifier

photo by Mario Gogh on Unsplash

With the development of Deep Learning frameworks, it’s more convenient and easy for many people to design the architecture for an artificial neural network. The 3 most popular frameworks, Tensorflow, Keras, and Pytorch, are used more frequently. To improve the performance of our neural networks, there are many approaches, e.g. improve the data quality, using data augmentation. However, data quality is the source of data science. To get better data quality is usually extra expensive, time- and human resource-consuming. Therewith, we prefer to handle the hyperparameters/parameters of a model🏄🏼.

Let’s start it!

1. Parameters or Hyperparameters

A model parameter is a configuration variable that…

A geographic demonstration of the web scraped Corona information in Germany with GeoPandas and Matplotlib

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In this story, I try to share my experience to make Corona information geo-visual with Python packages (Geopandas, pandas, Matplotlib). The Corona information is extracted by web scraping. Since web scraping is just not our aim but a method to get information, I won’t spend much time explaining this part of the code🌚.

Note from the editors: is a Medium publication primarily based on the study of data science and machine learning. We aren’t health professionals or epidemiologists. To learn more about the coronavirus pandemic, you can click here.

Social background: corona pandemic

As of 13 March 2020, when the number of new…

Yefeng Xia

🐳home-made Data-science student 👔👉🏼

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