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Welcome everyone to the deep learning course with the mini-series of Python and Tensorflow tutorials. Since I learned in DL with the TensorFlow course a little over 3 years ago, a lot has changed . I suggest to Getting started with the latest version of TF , isn't as complicated, and you don't need to know much to be successful with deep learning.
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BERT-Disaster-Tweets-Classification-

witter has become an important communication channel in times of emergency. The ubiquitousness of smartphones enables people to announce an emergency they’re observing in real-time. Because of this, more agencies are interested in programmatically monitoring Twitter (i.e. disaster relief organizations and news agencies). However, identifying such tweets has always been a difficult task because of the ambiguity in the linguistic structure of the tweets and hence it is not always clear whether an individual’s words are actually announcing a disaster.
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8

Positive-chatbot

Nowadays, chatbots has emerged in all domains and proved its efficiency in helping assistants saving time and managing interactions with customers. However, communicating with a conversational agent seems frustrating sometimes, especially when the goal of this chatbot is to help users to overcome their problems. That is why, NLP researchers has developed a new terminology that aims to make conversations with virtual assistants hat does not sound or behave like robots but as human like as possible. The tool which can enhance this is sentiment analysis. In this context, Pixemantic decides to include a Positive chatbot in its new platform called Dr.Happy, that aims to help users overcome their depression, anxiety, and daily-life problems.In order to achieve its goal, Pixemantic should have a solid dataset that allows to the chatbot to discuss in different topics with users and assist them with solutions for their issues. we will cover the main milestones of the preparation of the needed dataset for Positive chatbot
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This repository will help you to creat your first application in computer vision based on machine learning algorthims, thise two fields are become closely related to one another. Machine learning has improved computer vision about recognition and tracking. It offers effective methods for acquisition, image processing, and object focus which are used in computer vision. i built this application to detection then to recognize its lincence number plate which developed in GUI application based on Python software
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