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The Democratization ofArtificial Intelligence andDeep Learning
AbstractDeep learning is driving rapid innovations in artificial intelligence and influencing massive disruptions across allmarkets. This paper provides an understanding of the promise of deep learning, the challenges with leveragingthis technology, how it is currently solving real-world problems, and more importantly, how deep learning can bemade more accessible for data professionals as a whole.What is Deep Learning?Deep learning, which is a specialized and advanced form of machine learning, performs what is considered“end-to-end learning”. A deep learning algorithm is given massive volumes of data, typically unstructured anddisparate, and a task to perform such as classification. The resulting model is then capable of solving complextasks such as recognizing objects within an image and translating speech in real time.Deep learning models can be trained to perform complicated tasks such as image or speech recognition anddetermine meaning from these inputs. A key advantage is that these models scale well with data and theirperformance will improve as the size of your data increases.FEATURE EXTRACTION + CLASSIFICATIONOUTPUTCARNOT CARINPUTDEEP LEARNINGINPUTFEATURE EXTRACTIONCLASSIFICATIONOUTPUTCARNOT CARMACHINE LEARNING2
Deep learning not only performs best with larger volumes of data, but also requires powerful hardware such asgraphical processing units (GPUs) in order to perform. The deep learning market is expected to be worth $1.75billion by the year 20221. Investment in this area is driven by the fact that 61% of enterprises with an innovationstrategy are applying AI to their data to find previously missed opportunities such as process improvements ornew revenue streams2.Innovative Deep Learning UsesDeep learning has enabled innovation and transformation across a broad range of industries. From anomalydetection to video analysis, businesses have been able to leverage artificial intelligence to gain competitiveadvantage and even change the way their markets approach the customer experience.IMAGE CLASSIFICATIONThis is the process of an AI application identifying and detecting an object or a feature in adigital image or video. Image classification has taken off in the retail vertical which is usingdeep learning models to quickly scan and analyze in-store imagery to intuitively determineinventory movement. This has lead to streamlined operations, reduced costs, and new salesopportunities3.VOICE RECOGNITIONThis is the ability of a deep learning model to receive and interpret dictation or to understandand carry out spoken commands. Models are able to convert captured voice commands totext and then use natural language processing to understand what is being said and in whatcontext. This has delivered massive benefits to industries like automotive which uses voicecommands to enable drivers to make phone calls and adjust internal controls – all without

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Term
Spring
Professor
joseph
Tags
Artificial Intelligence, Machine Learning, Artificial neural network, deep learning

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