In our neighborhood, sometimes we celebrate, sometimes we need help. It is the neighbors who are always first there no matter the case. In our culture there is a saying ""When you are poor , neighbors will help; once you become rich, you'll be surprised by visits from (alleged) relatives afar. Being happy is one of the ultimate goal in life, and living in helpful and happy neighborhood is one of the steps of being happy. Community building is a necessity for happy life.

What it does

We help you to help your Neighbors in need. There are many problems in a society which cannot be mitigated by people alone. We have brought tech and community in one field to help empower the neighborhood. We help you feel happy by helping your Neighbors. You can also ask help from your neighbors. Our goal is to build a happy and helpful neighborhood.

How we built it

We have also used a large datasets and trained a model with an accuracy of 99% using the google cloud platform. The data is trained using deplaning module using LSTM followed by various layers of CNN architecture.

Challenges we ran into

Godaddy registry didn't work which make us to look for an alternative source to get domain. The datasets we used were very rough containing links, tags and unwanted words which were very difficult to identify and clean. Also to acquire best result we have to go through Bayes method, SVM and deeplearning method which is a very long task.

Accomplishments that we're proud of

We are able to make our neighborhood happy and peaceful. Friendly neighborhood makes our quality of life easier. We are proud to meet talented people from all around the world and compete in such a prestigious event.

What we learned

This hackathon make us able to work together, Develop an idea and implement it in short span of time. The best part we learned from this hackathon is time management. Working in both web development and machine learning part is a challenging task and also a fun part to learn. We learned to deploy an machine learning model using tensorflow.js.

What's next for Neighborhoodly Status

We will make the application available in several languages in future. We will follow principles of design and make specific type of application for specific community. We will also involve local authorities and organizations. For future, we will use data analysis and machine learning to predict and detect the threats and create alerts and for the people in Neighborhood. We want to create a gamification type interface where user feel comfortable to use the application.

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