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Optimize ML modeling using a timing decorator
Record the execution time of ML training using timing decorators and use it for productive data science and ML optimization Image source : Pixabay (Free to use) Why measuring time is important We can go on and provide hundreds of arguments and quotes showing why the act of measurement is important in science and technology. Here is a powerful one, One accurate measurement is worth a thousand (…)
Best front-end Python frameworks in 2021
Welcome back! Python is an awesome programming language with a ton of capability, one of these functions is building GUI’s (front-ends), so let’s talk about some of my favorite front-ends frameworks for Python. Now, Python is an awesome language for web development as well, if you want to see some sample websites you can build with Python, check out this article below: Let’s take a look at some (…)
How to Create Powerful Web Apps and Dashboards using Dash 2.0
Designing Multi-Page Web Apps using Python
How To Make HTTP Requests in Streamlit App
Utilizing requests or aiohttp packages Since its inception, Streamlit has been gaining immense popularity among developers for building data applications in Python. It released its official 1.0 version on Oct 5, 2021. For your information, Streamlit is — “… an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science.” — (…)
Tidy Time Series Forecasting in R with Spark
I’m SUPER EXCITED to show fellow time-series enthusiasts a new way that we can scale time series analysis using an amazing technology called Spark ! Without Spark, large-scale forecasting projects of 10,000 time series can take days to run because of long-running for-loops and the need to test many models on each time series. Spark has been widely accepted as a “big data” solution , and we’ll use (…)
Event sourcing using Kafka
When building an event sourced system, there’s a couple of options available when it comes to persistence. First is EventStore, a mature…
Using Data Science in Pharma – Top 10 Real-World Examples
Data science is advancing into nearly every industry from pharma and banking to sales and logistics. And why not — when data science is properly integrated it results in a performance boost, faster implementation, or process automation (read: money, money, money). The pharmaceutical and medical industries are no exception. Every top pharmaceutical company uses data […] Article Using Data Science (…)
Visualize Your Strava Data on an Interactive Map with Python
Use the Strava API with Python to download you activity data, create an elevation profile and plot your activity details on an interactive map in just a few easy steps. Image by Author Downloading your Strava data isn’t that complicated. But first, you will have to go through a one time manual process that grants your application access to all of your activity data. To get you started , I (…)
Level Up Your Python Code with Abstract Classes
How to implement abstract classes in Python, and why should we do it
How to Include R and ggplot in a Python Notebook
You can mix an match Python and R in the same Jupyter Notebook — here’s how Images from R’s ggplot2 in a Python notebook-image by author You are either an R person or a Python person, right? Unless, of course, you like some aspects of Python and others of R. So why not mix and match? For example, R’s ggplot2 is a great visualization package, so wouldn’t it be good to be able to use that in a (…)
Wątki i procesy w Pythonie
Wstęp Czymże byłoby programowanie bez współbieżności i równoległości. Watki i procesy to elementy budulcowe wspomnianego modelu a ich współistnienie i dostęp do współdzielonych danych, to potężna broń na drodze ku wydajności i efektywności kodu. Czasem niestety taki styl pisania programów… The post Wątki i procesy w Pythonie first appeared on Mateusz Mazurek – programista z pasją .
Statistics in Python — Using ANOVA for Feature Selection
Statistics in Python — Using ANOVA for Feature Selection Understand how to use ANOVA for comparing between a categorical and numerical variable In my previous article, I talked about using the chi-square statistics to select features from a dataset for machine learning. The chi-square test is used when both your independent and dependent variables are all categorical variables. However, what if (…)
18 Machine Learning Best Practices
In this article, we explore some of the best practices that you can apply when building your machine learning application.
How not to be lost with VSCode when coming from RStudio?
A few days exploring VSCode possibilities after multiple years developing with RStudio
Generate Automated Word Documents with Python
Automating the repetitive tasks that you shouldn’t be wasting time over
Time Series Forecasting Best Practices
Earlier this year, my colleague Vishal Sharma gave a talk about time series forecasting best practices. The talk was well-received so we decided to turn it into a blog post. Below are some of the highlights from his talk. You can also follow the two software demos and try it yourself using our H2O AI […] The post Time Series Forecasting Best Practices appeared first on H2O.ai .
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