Pandas VS tensorflow

Pandas is a go-to tool for tabular data management, processing, and analysis in Python, but sometimes you may want to go from pandas to SQL.

panda’s

> The big thing pandas has going for it is that it's already been through this field testing. All the bugs have been ironed out by the hundreds of thousands of users.

At this very moment pandas github repo has 1563 open issues labeled with a bug tag [0]. So much for "all the bugs have been ironed out".

[0] https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3...

Python is the main programming language I use nowadays. In particular numpy and pandas are of course extremely useful. I also use biopython package - a collection of software tools for biological computation written in Python by an international group of researchers and developers.

Below is the python Task that transforms the tweets list into a Pandas dataframe, then dumps it in our MinIO Object Storage as a CSV file:

It was rewarding to dig into SQLite a bit while solving this puzzle, so I figured this would be a good opportunity to learn a bit more about pandas too! So how would I adapt this working SQL solution to pandas?

All the data has been extracted from the official Tor Metrics website, and using Python with the Pandas library I've cleaned the data. Finally, the visualizations have been made with Tableau.

If you did that you could use a built-in library like csv to read and parse the file or you could use a 3rd party library like Pandas. Alternatively, you could store your file as json:

Tensorflow 238k contributors

C++ is actually used in machine learning. More than 60% of TensorFlow code is in C++: https://github.com/tensorflow/tensorflow. With high level configs and prototyping is done in python.

10. Tensorflow

> In practice, scientific computing users rely on the NumPy family of libraries e.g. NumPy, SciPy, TensorFlow, PyTorch, CuPy, JAX, etc..

this is a somewhat confusing statement. most of these libraries actually don't rely on numpy. e.g. tensorflow ultimately wraps c++/eigen tensors [0] and numpy enters somewhere higher up in their python integration

[0] https://github.com/tensorflow/tensorflow/blob/master/tensorf...

``` Downloading data from https://github.com/openai/CLIP/blob/main/clip/bpe\_simple\_vocab\_16e6.txt.gz?raw=true 1356917/1356917 [==============================] - 0s 0us/step WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/pyct/static_analysis/liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23. Instructions for updating: Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089 By using this model checkpoint, you acknowledge that its usage is subject to the terms of the CreativeML Open RAIL-M license at https://raw.githubusercontent.com/CompVis/stable-diffusion/main/LICENSE Downloading data from https://huggingface.co/fchollet/stable-diffusion/resolve/main/kcv\_encoder.h5 492466864/492466864 [==============================] - 7s 0us/step Downloading data from https://huggingface.co/fchollet/stable-diffusion/resolve/main/kcv\_diffusion\_model.h5 3439090152/3439090152 [==============================] - 85s 0us/step Downloading data from https://huggingface.co/fchollet/stable-diffusion/resolve/main/kcv\_decoder.h5 198180272/198180272 [==============================] - 3s 0us/step ``` I attempted to save the model from Keras_cv but it throws the same error.

Python 3.11 is worse. It doesn't even support Tensorflow (at least as of now), which is arguably the most popular deep learning package in Python.

So, clearly with your AP CS class and PLC logic knowledge, if you were dumped into a codebase like Hadoop, QT, or TensorFlow you'd be able to quickly and competently analyze what is going on with that code, understand all the libraries used, know the reasons why certain compromises were made, and be able to make suggestions on how to restructure the code in a different way? Because I've been programming for coming up on two decades and unless a system is within the domains that I have experience in, I would not be able to provide any useful information without a massive onboarding timeline, and definitely wouldn't be able to help redesign anything until actually coding within the system for a significant amount of time.

It seems like Tensorflow 2.11 is dropping official native support for Windows. I was trying to compile TF 2.11-rc1 on Windows but hit with an error which I have reported here (https://github.com/tensorflow/tensorflow/issues/58323). They told me to refer to the release note (https://github.com/tensorflow/tensorflow/blob/v2.11.0-rc1/RELEASE.md#major-features-and-improvements)