Machine Learning Path

Exploreka: The Exploreka app is a platform designed to help users find and plan their travel journeys, including a range of available travel packages. The app provides up-to-date information on tourist destinations, activities, and accommodations, as well as digital reservation and payment capabilities. Exploreka also features a standout 360 virtual tour to enhance tourist interest and improve the travel planning experience. The app offers personalized recommendations based on user interests and preferences. Its goal is to promote sustainable tourism practices by facilitating interactions between tourists and local communities. This will encourage tourists to explore more remote destinations, thus promoting a more equitable distribution of tourist visits.

Machine Learning Features

Exploreka, our tourism application, incorporates advanced machine learning capabilities to provide personalized recommendations and intelligent decision support to users. With our machine learning feature, we have implemented the following key components:

• Content-Based Recommendation System Exploreka utilizes a content-based recommendation system powered by machine learning algorithms. This system analyzes the content, attributes, and characteristics of various tourist destinations, activities, and accommodations. Based on a user's preferences, past interactions, and profile information, the system suggests relevant recommendations tailored to their interests. By considering factors such as location, theme, reviews, and ratings, our content-based recommendation system ensures that users receive personalized recommendations that align with their preferences.

• Collaborative Filtering In addition to the content-based recommendation system, Exploreka incorporates collaborative filtering techniques. This mechanism leverages the collective wisdom of our user community to provide enhanced recommendations. By analyzing user behavior, such as ratings, reviews, the system identifies similar user profiles and makes recommendations based on the preferences of similar users. Collaborative filtering enables users to discover hidden gems, popular attractions, and experiences that align with their interests, thereby enhancing their overall travel experience.

• Decision Support System Exploreka's machine learning feature also includes a decision support system. By considering factors such as location, budget constraints, rating, and category, the decision support system assists users in making informed decisions.

With the integration of content-based and collaborative recommendation systems, as well as a decision support system, Exploreka's machine learning feature offers a personalized and intelligent approach to tourism. By leveraging the power of machine learning, users can discover new destinations, tailor their travel experiences, and make well-informed decisions. Exploreka aims to enhance user satisfaction, engagement, and overall enjoyment of their travel journeys.

Dataset

To build a recommendation system, we use the dataset on kaggle here

Acknowledgements

• Building A Collaborative Filtering Recommender System with TensorFlow
• Collaborative Filtering Recommendation System Using TensorFlow with Neural Net
• Recommendation System Dengan Python : Content Based Filtering (Part 2)
• Building a Content Based Recommender System for Hotels in Seattle
• An Exhaustive Guide to Decision Tree Classification in Python 3.x

How to Use

1. Open Folder Notebook/DEPLOY FIX ALL
2. Clone to your local repo
3. fill file .env with your requiremennt
4. open CMD then input command pip install -r requirements.txt
5. after that input commamd python main.py

Documentation

Exploreka Machine Learning Documentation API