🌠🌈Classificação de Corpos Celestes usando suas características espectrais🌐☄️
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Updated
May 28, 2024 - Jupyter Notebook
🌠🌈Classificação de Corpos Celestes usando suas características espectrais🌐☄️
How weather directly impacts renewable energy generation.
End to End MLOps with Berka Bank Dataset and VertexAI
repo contains sample code snippets on #ML, #DeepLearning, #GenAI topics
The aim is to build a predictive model that can accurately classify whether the employee is likely to leave or the employee is likely to stay in the company. This allows companies to take proactive measures, such as improving working conditions, offering promotions, or addressing dissatisfaction, to retain valuable employees.
This Repository contains material to learn about machine learning algorithms concepts along with implementation. This also provides you the material to prepare yourself for interviews.
Prediction of loan status based on training ML models on historical data and predict status, complete with thorough Data Visualization and Exploratory Data analysis
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
for various machine learning projects
Machine Learning.
Task-1 Completed as a DSBA Intern @ The Sparks Foundation
Sort & Slice: A Simple and Superior Alternative to Hash-Based Folding for Extended-Connectivity Fingerprints
Exploring QSAR Models for Activity-Cliff Prediction
DU - DA Module 20 challenge
Free lectures on Machine learning which covers core topics and models on supervised and unsupervised, machine learning.
AI | ML | DL Fully Covered for Basic
The repository contains a set of machine learning supervision algorithms implemented to better understand the fundamental concepts behind machine learning. These algorithms aim to facilitate the development of an in-depth understanding of the underlying principles and techniques of machine learning.
The projects here demonstrate how a textual corpus is prepared for analysis, preprocessing steps for computational text mining and extraction of business insights. Concepts such as feature representation using bag of words and TF-IDF are demonstrated, clustering and supervised machine learning algorithms like regression and others are used on a DTM
The code related to my M.Sc. Data Science thesis at the University of Helsinki.
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