Data Analytics & Deep Learning

Deep Learning: Age of Learning

       Deep learning is an advanced tier of artificial intelligence that utilizes data and algorithms to make predictions and solve problems. To be able to grasp the concept of deep learning, a rudimentary understanding of machine learning is required. Machine learning enables a computer to learn and solve problems. Essentially, developers write a program which enables the computer to solve a given problem, without outlining the steps required to solve the problem. During the process of machine learning, the computer goes through a trial and error process, which it utilizes to eventually reach a conclusion. Deep learning uses the methodology of machine learning and the implementation of algorithms and integrates these processes further by creating multiple levels of what’s called a neural network. This environment allows the program to simulate three different types of analysis involved in the learning process: supervised, unsupervised, and reinforcement.

Deep learning applies the fundamental concepts introduced in Temple’s Data Analytics course. Concepts like data extraction, data transformation, and data loading, as well as predictions based on big data analytics. Applying algorithms along with the datasets provided to the environment, the deep learning program constantly extracts data from the datasets, transforms the data, and generates conclusive metrics to determine whether the effectiveness of a hypothesis. The program records successful performances and constantly builds off its successes to create a smaller margin of error.

Deep learning methodologies are implemented and utilized in many technologies of today, and tomorrow. For instance, Google’s Android OS utilizes deep learning in its voice-command software, allowing the software to adapt and better assist the users. Deep learning’s potential is fascinating and holds a promising future for technological advancement.



Hof, R. D. (2016, March 29). Deep Learning With massive amounts of computational power, machines can now recognize objects and translate speech in real time. Artificial intelligence is finally getting smart. Retrieved April 18, 2017, from

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  • Active AIS member
    Spring 2017

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  • AIS professional development workshop
    Spring 2017