<케라스 창시자에게 배우는 딥러닝 2판> 도서의 코드 저장소

R interface to Keras Tuner

<개발자를 위한 머신러닝&딥러닝> 도서의 코드 저장소

Simple integration of keras-tuner (hyperparameter tuning) and tensorboard dashboard (interactive visualization).

Extension for keras tuner that adds a set of classes to implement cross validation techniques.

Training neural networks to classify network traffic by L7 protocol.

This is sample repos for how to use Keras Tuner to perform hyper-parameter tuning in Databricks.

In this repository I have utilised 6 different NLP Models to predict the sentiments of the user as per the twitter reviews on airline. The dataset is Twitter US Airline Sentiment. The best models each from ML and DL have been deployed. It employs text preprocessing,

Using Hybrid model based on LSTM we predict the daily closing price of the index based on the historical data available. Using KerasTuner These models were trained, and automatically evaluating different components and design decisions, and their results were measured. Finally, we analyzed and clustered our results in order to know the character…

Final project of "Image Processing for Computer Vision" course.

This repository contains demo implementations for using keras tuner to tune hyperparameters of models in keras and scikitlearn. Additionally, it includes how to generate the visualization in Tensorboard.

Recommender systems became one of the essential areas in the machine learning field. Product recommendations are key to enhance customer exeperiance and help them to find the right product from huge corpus of products. When customer find the right product that are mostly like going to add the item to cart and which help in company revenue.

Development and comparison of 12 machine learning models to predict autism as well as a discussion of the process.

Our project leverages Python, pandas, Tableau, and machine learning techniques to analyse and predict student outcomes in higher education. Using a comprehensive dataset, we employ data preprocessing, visualisation with Tableau, and advanced machine learning models built with Python to uncover insights into graduation rates and factors influencing

Deep Learning model for predicting success of venture capital recipients

Predicts weather of your city on the basis of input paramters provided.

Preprocessing data and building some models to predict passengers survival chances.

Analysis of over 34,000 businesses that received funding, to generate 184 Neural Network algorithm to predict effective allocation of funding.

A small project using Keras and Keras Auto-Tuner API to build a logistic regression model to predict whether a user will purchase an item or not based on historic user data on Age, Gender, Salary and Purchase Status

Convolutional Neural Network Architecture to classify Bone Fractures from X-Ray Images