One of the most exciting areas of data science is the growing field of deep learning. With an explosion of compute power combined with accessible tools such as TensorFlow, complex concepts such as computer vision, natural language processing, and time series predictions can all be approached with deep learning. Andrew Ng, the co-founder of coursera.org and founder of DeepLearning.AI, is one of the worlds leading data science researchers and educators. His team put together a great Deep Learning Specialization taking a deep dive into the inner workings of building neural networks from scratch.

It was a great challenge building a neural network using numpy, but it was extremely educational understanding the inner workings of a deep learning model as well as the methods used to improve and optimize these models. After committing full 10-hour workdays to the specialization I quickly recieved my certification. Verify here.

Deep Learning is the next frontier of machine learning. Simple, supervised learning models have been deployed successfully throughout many industries. The ability to digest unstructured data and process into useful insights is critical. The intersection of human and computers becomes even more blurred with the improvements in facial and speech recognition models. Deep learning, otherwise known as Artificial Intelligence is changing the world around us every day in ways that have already become taken for granted.

Following up this specialization I have been inspired to pursue deep learning with much more focus. I will be preparing for the Google TensorFlow Professional Certification exam in the coming weeks and look forward to sharing my proejct with various computer vision, NLP, and other deep learning projects!