Learn about deep learning from Mammalz's Head of Data Science Stephen Cobb! The future of AI is now and Mammalz is riding the wave! 🌊
As we get closer to Mammalz official launch date we are working on implementing multiple types of AI into the platform. We want to make the Mammalz experience awe-inspiring, but beyond just the experience, we also want further the Mammalz mission. Mammalz will be utilizing machine learning and neural networks, however, a specific type of AI we are truly excited about is deep learning.
What is deep learning?
Deep learning is a type of AI in the category of neural networking. This process was developed to be reflective of how the human brain works. Just like the human brain, it requires time to train and an incredibly large labeled data set for it to become effective. It achieves this by filtering through layers of information in increasingly complex calculations resulting in the ability to generate predictive analytics.
What are the main tools for using deep learning?
Since deep learning requires vast amounts of labeled data and high preforming GPU’s, building a server to store and run these processes is one of the fundamental tools required for using deep learning. Software to build the network completely depends on the language, architecture, and type of data being processed. Each framework has its own positives and negatives, so choose one that works for your needs.
What are the pros and cons of deep learning?
The limiting factors when choosing between machine learning and traditional neural networks is the GPU ( graphic processing unit ) performance and the amount of labeled data. Without either of these, the accuracy and speed of evolutionary learning are reduced dramatically. However, when you have a robust system and incredible amounts of labeled data, the results are staggering. This is what has been a driving factor in new innovations such as, self-driving cars and new diagnosis systems in the Healthcare industry.
What is deep learning used for?
Deep learning is currently being used extensively in image, natural language, voice and pattern recognition. This has led to new generations of self-driving cars, virtual assistance, and even predictive analytics in the financial sector and healthcare industry. Mammalz will be using deep learning to recognize migration patterns, endangered ecosystems, and even preventing wildlife trafficking through encrypted data.