Florence is a Python-based computational framework for the numerical simulations of multi-physics problems using the finite element methods.

Florence supports all major operating systems including Linux, macOS and Windows (under Cygwin/MinGW) under
• Python 2.7
• Python >= 3.5
• PyPy >= v5.7.0


pip install Florence


Doc : https://github.com/romeric/florence/wiki/1.-Getting-started-with-Florence

Do you know what is IIFE in Python ?

IIFE - immediately invoked function execution:

Which you can use in lambda expression passing args values immediate right to expression.


(lambda x, y, z: x + y + z)(1, 2, 3)


Note : IIFE is actually concept from JavaScript

⌛⌛When you understand Underscores in Python, You will be knowing following concepts as well.

◌Name Mangling
◌Private variables (there is no private variables )
◌Dunder or Special or Magic methods
◌Usage of _ (underscore) for variable

In near future, you can raise groups of exceptions at a time in Python.

A new grammar feature, except*, will allow multiple except clauses to match and execute.


A single ExceptionGroup can cause several except* clauses to execute, but each such clause executes at most once (for all matching exceptions from the group) and each exception is either handled by exactly one clause (the first one that matches its type) or is reraised at the end.

Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.


pip install metaflow


A framework for real-life data science

https://youtu.be/TATmeEFdLuI


This is yesterday’s recorded session


Check resources links in video description


30 AI and Datascience Resources

Everyweek we will be connecting for DataScience Dialogue. We discussed AutoML and DataRobot Demo #2 in this week. I have demonstrated the DataRobot which market leading AutoML tool.

Unicorn - A Magical Full-stack Framework for Django - My Talk #2 https://youtu.be/UlFcUXxYSto

Machine learning steps:


Analyze the problem
Gather the data
Prepare the data
Choose the right model
Train the model
Evaluate the results
Look for biases
Tune it
Deploy the model
Monitor it
Retrain it

Fixing overfitting:

Simplify the model (fewer parameters)
Simplify training data (fewer attributes)
Constrain the model (regularization)
Use cross-validation
Use Early stopping
Build an ensemble
Gather more data

Fixing underfitting:

More complex model (more parameters)
Increase number of features
Feature engineer should help
Unconstrain the model (no regularization)
Reduce noise on the data
Train for longer

The common convolutional neural networks (CNN).

LeNet-5
AlexNet
VGG-16
Inception-v1
Inception-v3
ResNet-50
Xception
Inception-v4
Inception ResNets
ResNext-50

YAML- Introduction, Read and Write YAML files using Python Script - Talk #3 https://youtu.be/XrPwTkyoBok

This is an important configuration file for deployment AI models and DevOps configurations