Inspiration
Deforestation ranks among the most pressing environmental challenges of our era, imperiling ecosystems, economies, and our way of life. Our project's mission is to combat deforestation through vigilant monitoring, seeking to preserve the Earth's vital forests, mitigate ecological imbalances, and protect our global climate.
What it does
The approach involves comprehensive data collection from diverse sources, data preprocessing, feature engineering, and statistical analysis. Predictive modeling and the development of early warning systems aid in understanding and forecasting habitat losses.
How we built it
These are steps we followed to build the Habitat loss control.
1.Collecting Data: We used kaggle to build our dataset. 2.Data cleaning and preparation: We first removed the unwanted images and then performed resizing and scaling of the images. 3.Choosing and Training the Model.
Challenges we ran into
The main challenge we ran into was about selecting and collecting the dataset. Since collecting data is the most important part of a Data Science/ Machine Learning project/ AI project , we decided to use kaggle. We had to give a lot of thought on selecting which type of dataset would be the most useful and help us correctly classify the data. We finally decided to gather data from google images, due to the bulk availability of images, and good proportion of both accurate and not so accurate images for each class.
Accomplishments that we're proud of
1.We were able to select a project which is useful. 2.Worked and enjoyed the IBM z Datathon event.
What we learned
How important it is to work in a team. How important is data gathering and the value of a dataset. Why data cleaning and data preparation is very important. How to use Machine Learning, Deep Learning and Data science libraries to the best to create a model. How to use the IBM Linux0NE features like - Docker Containers, tools like Python and Juptyer and libraries like Tensorflow and Keras.
What's next for A Comprehensive Strategy to Combat Habitat Loss
1.Improving the accuracy of our model. 2.Building a website, which provide information on habitat species and their movements.
Log in or sign up for Devpost to join the conversation.