When Kaggle finally launched a new tabular data competition after all this time, at first, everyone got excited. Until they weren’t. When the Kagglers found out that the dataset was 50 GB large, the community started discussing how to handle such large datasets [4]. CSV file format takes...
Notebooks combine computer code (such as Python, SQL, or R), the output from running the code, and rich text elements (formatting, tables, figures, equations, links, etc.) in a single document. The key benefit of notebooks is the ability to include commentary with your code. That means...
And to work on real-world projects, you need to find the relevant data to explore. For this, there are various online platforms that you can refer to like:Kaggle –A community platform for data science discovery and collaboration that includes datasets, contests, and tools. UCI Machine ...
reducing the time and resources required to train a model from scratch. This can be especially useful when working with small datasets that may not contain enough information to train a model
In a Jupyter Notebook, the command becomes:Python !python -m pip install polars Either way, you can then begin to use the Polars library and all of its cool features. Here’s what the data looks like:Python >>> import polars as pl >>> tips = pl.scan_parquet("tips.parquet") >...
Hands-on Time Series Anomaly Detection using Autoencoders, with Python Data Science Here’s how to use Autoencoders to detect signals with anomalies in a few lines of… Piero Paialunga August 21, 2024 12 min read 3 AI Use Cases (That Are Not a Chatbot) ...
The examples throughout this article use the Uber Fares Dataset available on Kaggle.com. Download the CSV to follow along. It has nine columns and 200k rows. These are the fields we will use: key — a unique identifier for each trip fare_amount — the cost of each trip in usd...
It now powers many popular AI applications and services in companies like Tesla, Microsoft, OpenAI, and Meta. If you're new to PyTorch, start your journey with the Data Engineer in Python track to build the foundational Python skills essential for mastering deep learning. Get certified in your...
In this section, we will look into various methods available to install Keras Direct install or Virtual Environment Which one is better? Direct install to the current python or use a virtual environment? I suggest using a virtual environment if you have many projects. Want to know why? This ...
Consider downloading public datasets from sources like Kaggle or government data portals to create meaningful analytics projects. This hands-on experience will help solidify your understanding of Snowflake's capabilities and prepare you for real-world challenges you'll face in production environments. ...