A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.
My Tensorflow Notebook. In this notebooks I have implemented various kind of model optimisation techniques.
A series of documented Jupyter notebooks implementing polynomial regression models and model performance analysis
Jupyter notebook script with a two parameter monthly water balance model, based on (Xiong,1994)
Cómo cambia la exactitud de un modelo, al usar diferentes capas de convolución y modificar el número de épocas y baches
The objective of this project is to develop a machine learning model that can effectively classify emails as spam or non-spam (ham) based on their content.
All models, notebooks related to BotaniScan are here.
Notebooks, code and data for visualization of data and creating prediction models by extracting useful data. Consists of notebooks from all fields of study including telecom and medical fields.
My learning on the AI field also working on several Google Colab Notebooks
Simple Emotion Detection using Machine Learning
For the purposes of familiarization and learning. Consists of utilizing LangChain framework, LangSmith for tracing, OpenAI LLM models, Pinecone serverless vectorDB using Jupyter Notebook and Python.
This repository has scripts that perform model weighting using various methods, plots the model weights and corresponding maps, and estimates RMSE of each model. The provided notebooks are flexible and allow users to make edits as desired (e.g. choice of CMIP6 models, choice of variables, etc).
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