Generative Adversarial Networks test from Coursera's Advanced Machine Learning. Executed on Colab.
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Updated
Mar 12, 2019 - Jupyter Notebook
Generative Adversarial Networks test from Coursera's Advanced Machine Learning. Executed on Colab.
The code I wrote for a Coursera specialization in Advanced Machine Learning. Each folder only contains graded assignments.
This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms,…
Solved programming exercises from the Advanced Machine Learning specialization by National Research University on Coursera.
breast cancer classification with advanced machine learning technique
Code from Coursera Advanced Machine Learning specialization - Intro to Deep Learning - week 2.
[ETH Zurich] My projects for the module "Advanced Machine Learning" at ETH Zürich (Swiss Federal Institute of Technology in Zurich) during the academic year 2019-2020.
Advanced ML Project : An Orca Call classifier using mel-spectrograms as audio representations to detect Killer whales
Week 1 assignment form Coursera's "Advanced Machine Learning - Introduction to Deep Learning"
Applying Advanced Machine Learning techinques such as pipelines and text mining, as well as advanced data engeneering methods like column transformers and estimators.
Final Project for CS 9860A- Advanced Machine Learning; using regression techniques to predict housing prices using the House Price- Advanced Regression Techniques Kaggle dataset
An advanced feature engineering and model building techniques
Road traffic sign recognition and detection with use of OpenCV, ROS and Arduino build up robot
Repository for the National Research University Higher School of Economics - Advanced Machine Learning Specialization on Coursera
This report proposes an approach to detect anomalies in credit card data using machine learning techniques. Credit card data is prone to fraudulent transactions, and detecting anomalies can help minimize financial losses. The proposed approach involves preprocessing the data by removing missing values and outliers
HealthProSpec is an advanced machine learning model developed for the Hackathon TechGig Code Gladiators organized by Doceree. The primary objective of HealthProSpec is to accurately predict whether a user is a Healthcare Professional (HCP) and, if so, identify their specific specialization.
Classification of flowers from Oxford Flowers 102 dataset
📚 This repository is my personal data science learning hub. Explore my journey from the very basics to advanced techniques. Dive into Python, data manipulation, analysis, visualization, and machine learning. Join me as I learn, grow, and experiment in the world of data science.
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