{"action":"created","issue":{"url":"https://api.github.com/repos/PyDataPune/Talks/issues/17","repository_url":"https://api.github.com/repos/PyDataPune/Talks","labels_url":"https://api.github.com/repos/PyDataPune/Talks/issues/17/labels{/name}","comments_url":"https://api.github.com/repos/PyDataPune/Talks/issues/17/comments","events_url":"https://api.github.com/repos/PyDataPune/Talks/issues/17/events","html_url":"https://github.com/PyDataPune/Talks/issues/17","id":427331535,"node_id":"MDU6SXNzdWU0MjczMzE1MzU=","number":17,"title":"Haptic Learning : inferencing human features using deep 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providing haptic feedback, users have been dependent on external devices including buttons, dials, stylus or even touch screens. The advent of machine learning along with its integration with computer vision has enabled users to efficiently provide inputs and feedback to the system. A machine learning model consists of an algorithm which draws some meaningful correlation between data without being tightly coupled to a specific set of rules. It's crucial to explain the subtle nuances of the network also the use-case we are trying to solve. The main question, however, is to discuss the need to eliminate an external haptic system and use something which feels natural and inherent to the user.\r\nTo connect the dots, we will talk about the development of applications specifically aimed to localize and recognize human features which could then, in turn, be used to provide haptic feedback to the system.\r\nThese applications will range from recognizing digits, alphabets which the user can 'draw' at runtime; developing state of the art facial recognition system; predicting hand emojis along with Google's project of 'Quick, Draw' of hand doodles.\r\nIn this presentation, we will discuss the development of such applications using computer vision techniques to minimize CPU utilization. First, we will start with formulating and addressing a strong problem statement followed by a thorough literature review. Once these things are taken care of, we will discuss the data gathering part, followed by the algorithm evaluation and future scope. By the end of the session, the audience will have a clearer understanding of building vision based models along with emphasis to contribute to the open-source community.  "},"comment":{"url":"https://api.github.com/repos/PyDataPune/Talks/issues/comments/506461974","html_url":"https://github.com/PyDataPune/Talks/issues/17#issuecomment-506461974","issue_url":"https://api.github.com/repos/PyDataPune/Talks/issues/17","id":506461974,"node_id":"MDEyOklzc3VlQ29tbWVudDUwNjQ2MTk3NA==","user":{"login":"akshaybahadur21","id":22640610,"node_id":"MDQ6VXNlcjIyNjQwNjEw","avatar_url":"https://avatars2.githubusercontent.com/u/22640610?v=4","gravatar_id":"","url":"https://api.github.com/users/akshaybahadur21","html_url":"https://github.com/akshaybahadur21","followers_url":"https://api.github.com/users/akshaybahadur21/followers","following_url":"https://api.github.com/users/akshaybahadur21/following{/other_user}","gists_url":"https://api.github.com/users/akshaybahadur21/gists{/gist_id}","starred_url":"https://api.github.com/users/akshaybahadur21/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/akshaybahadur21/subscriptions","organizations_url":"https://api.github.com/users/akshaybahadur21/orgs","repos_url":"https://api.github.com/users/akshaybahadur21/repos","events_url":"https://api.github.com/users/akshaybahadur21/events{/privacy}","received_events_url":"https://api.github.com/users/akshaybahadur21/received_events","type":"User","site_admin":false},"created_at":"2019-06-27T18:35:28Z","updated_at":"2019-06-27T18:35:28Z","author_association":"NONE","body":"@PyDataPune - \r\nBio : My interest in computer science sparked when I was working on a women's safety application aimed towards the women welfare in India and since then I have been incessantly working on improving my skills. I stumbled upon machine learning then. I have made several open-source contributions in the field of ML and would continue to do so. I have made successful prototypes like an autonomous car, alphabet recognition, cancer classification, gesture recognition using learning models. These prototypes showcase the power of deep learning and how I can help your organization implement learning models to solve business cases. My ambition is to make valuable contribution towards the ML community and leave a message of perseverance and tenacity. Currently, I am working as a software engineer at Symantec, India. I am also deeply influenced by literature especially Shakespeare's work."}}
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