Original Source Here Facial Emotion Classification Photo by Lewis Osborne on Dribbble Human beings do have a lot of emotions and we as humans are able to distinguish between all of them. What if I tell you that we can expect some sort of same results from an ‘emotion-less machine. KERAS In this article, we will be talking about the use of the deep learning model in classifying two different emotions at a time. However, this thing can any day be extended to multi-class classification. In this project of mine, I h a ve worked on Keras, and I have handpicked some images to make the dataset from scratch, feel free to use a pre-defined dataset of your choice. PREPROCESSING For the very initial steps, let’s just import the necessary libraries and the dataset. Next, we are using images from tensorflow.keras.preprocessing to load and play around with images. For the next steps, we are just defining variables to store the path of the directories we will be mainly be work...

https://miro.medium.com/max/1200/0*NPC_xE-m9WzYZJHy Original Source Here Reading Our Minds: the A.I. Way The advancement of new technologies progresses at a staggering rate; so much so that it seems like in the blink of an eye the newest state-of-the-art becomes yesterday’s news. This holds more true for artificial intelligence, known as A.I., that has seen rapid development and huge successes within the past decade alone. From smartphones to self-driving cars, technology is consistently pushing the boundaries of what we believed to be previously impossible into tangible reality with real-world applications, and this advancement only continues. But will it continue to progress to the point where it can read our minds? Photo by Rami Al-zayat on Unsplash Man y of these advancements come to be through work done progressing the power of deep learning. Deep learning is a subset of machine learning that structures its model architecture in an artificial neural network manner,...

Original Source Here Analyse des sentiments avec BERT a l’aide de Hugging Face Source https://explore.mathworks.com/ Dans cet article, on va apprendre à entrainer BERT pour l’analyse des sentiments. Vous effectuerez le prétraitement de texte requis (tokens , padding et masques d’attention),aussi on va construire un classifieur de sentiments en utilisant l’incroyable bibliothèque Transformers de Hugging Face ! Vous apprendrez à : Comprendre intuitivement ce qu’est BERT. traiter les données textuelles pour BERT et construire un ensemble de données PyTorch (dataset). Utiliser le Transfer Learning pour construire un classifieur de sentiments en utilisant la bibliothèque Transformers de Hugging Face. Évaluer le modèle sur des données de test. Prédire le sentiment sur du texte brut Qu’est-ce que BERT ? BERT (Bidirectional Encoder Representations from Trans f ormers) est un modèle qui représente un bloc encodeur d’un transformateur et qui est pré-entraîné avec un énorme...

https://venturebeat.com/wp-content/uploads/2021/01/cloud-database-GettyImages-969567772-e1627330470267.jpg?w=1200&strip=all Original Source Here All the sessions from Transform 2021 are available on-demand now. Watch now. Eight out of ten IT professionals reported that their company’s usage of cloud technology increased during the pandemic, according to a new global research survey by ManageEngine . The survey focused on trends related to artificial intelligence (AI) , business analytics , and technology. With organizations increasingly supporting a distributed workforce, IT personnel are more willing than ever to invest in new technologies. Security, reliability, and price  were the top three drivers behind organizational decisions to adopt new technologies. The survey also found that organizations are using tools that facilitate business analytics and data-driven decision-making. The vast majority (89%) of respondents indicated that their reliance on business ana...

https://miro.medium.com/max/1200/0*8f8gYlpNM-JFX3zG Original Source Here 3 Rookie Mistakes To Avoid When Building Your Data Science Portfolio Here’s what to do and what to avoid Photo by Magnet.me on Unsplash Can you remember the last time you got a job just by submitting your resume? That’s right; the technical field has been restructured to a high revolutionized standard whereby employers no longer believe in a document (your resume) filled with experiences and grades from your educational background. They want to see what you can do or have done with the skills you possess. The capability to show your would-be employers what you can do, instead of just telling, is very paramount to clinching every job opportunity. Now here’s the catch, it’s not just about building a portfolio — you need to build one that will get you hired immediately. There are lots of beginner mistakes most data professionals make when building their portfolios. These mistakes usually disqualify th...

Original Source Here Déployer un projet de Deep Learning en production avec Keras et Flask Ce guide vous permettra de déployer un modèle de Machine Learning en partant de zéro. Source : https://explore.mathworks.com/ Définir l’objectif/le but Il est évident que vous devez savoir pourquoi vous avez besoin d’un modèle de Machine Learning (ML) en premier lieu. La connaissance de l’objectif vous donne des indications sur : Le ML est-il la bonne approche ? De quelles données ai-je besoin ? À quoi ressemble un “bon modèle” ? Quelles métriques puis-je utiliser ? Comment puis-je résoudre le problème maintenant ? Quelle est la précision de la solution ? Combien cela va-t-il coûter pour faire fonctionner ce modèle ? Dans notre exemple, nous essayons de prédire le prix des annonces Airbnb par nuit à New York. Notre objectif est clair : étant donné certaines données, nous voulons que notre modèle prédise le coût de la location d’une propriété par nuit. Chargement des données...

Original Source Here Deep Learning: Run Pytorch+FastAI trained model on Android by usingPytorch Mobile (also applicable to iOS) Introduction In this brief blog entry I will train a simple classifier using the FastAI library and explain how to run it on a simple demo Android App by using Pytorch Mobile . Always follow the links for guides and more info . If you are non-beginer with deep learning and FastAI, please get straight to the point and go to [Let’s do it] section. If you don’t know anything about Android it’s ok (I didn’t when I start writing this). The app will allow the user to upload an image from the gallery and classify between cat and dog. It will do it natively, processing it on the device. Preconcepts Totally avoid these sections if you know what the subtitle topic is. Pytorch A tensor l i brary using GPUs and CPUs . Similar to TensorFlow but better designed because it’s much pythonic, much more flexible, and equally faster. Mainly designed for deep le...