JLD2.jl
Pandas
JLD2.jl | Pandas | |
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2 | 397 | |
525 | 42,039 | |
1.7% | 0.7% | |
8.1 | 10.0 | |
10 days ago | 2 days ago | |
Julia | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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JLD2.jl
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Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
First, you need to save the model from the notebook to a file. For this you can use JLD2.jl module. This module used to serialize Julia object to HDF5-compatible format (which is well known by Python data scientists) and save it to a file.
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Best format to save matrices to a text file? (R interop)
I didn't realize this was the Julia subreddit. HDF5 or multiple CSV files would be my suggestion. As a side note, check out the JLD2 package. It's a HDF5 compatible format where the package is written in pure Julia.
Pandas
- PDEP-13: The Pandas Logical Type System
- PHP Doesn't Suck Anymore
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.
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Pandas reset_index(): How To Reset Indexes in Pandas
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method.
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Deploying a Serverless Dash App with AWS SAM and Lambda
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
[1]: https://github.com/pandas-dev/pandas/issues/53999
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Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
What are some alternatives?
julia - The Julia Programming Language
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
Chain.jl - A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
tensorflow - An Open Source Machine Learning Framework for Everyone
Plots.jl - Powerful convenience for Julia visualizations and data analysis
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Rocket.jl - Functional reactive programming extensions library for Julia
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
StatsWithJuliaBook
Keras - Deep Learning for humans
PlotDocs.jl - Documentation for Plots.jl
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration