Artificial Intelligence (AI) and Deep Learning are two main subjects in today's digital life.

In recent posts, we've been exploring essential torch functionality: tensors, the sine qua non of every deep learning framework; autograd, torch's implementation of reverse-mode automatic differentiation; modules, composable building blocks of neural networks; and optimizers, the – well – optimization algorithms that torch provides. But we haven't really had our "hello world" moment yet, at least not if by "hello world" you mean the inevitable deep learning experience of classifying pets. We'll distinguish ourselves by asking a (slightly) different question: What kind of bird? How to apply transforms, both for image preprocessing and data augmentation. How to use Resnet (He et al. 2015), a pre-trained model that comes with torchvision, for transfer learning.

Most data organisations hold is not labeled, and labeled data is the foundation of AI jobs and AI projects. "Labeled data, means marking up or annotating your data for the target model so it can predict. In general, data labeling includes data tagging, annotation, moderation, classification, transcription, and processing." Particular features are highlighted by labeled data and the classification of those attributes maybe be analysed by models for patterns in order to predict the new targets. An example would be labelling images as cancerous and benign or non-cancerous for a set of medical images that a Convolutional Neural Network (CNN) computer vision algorithm may then classify unseen images of the same class of data in the future. Niti Sharma also notes some key points to consider.

Deep Learning DevCon 2020 (CVDC) is a 2 days influential conference. Despite deep learning being such a specific subarea of ​​artificial intelligence & machine learning, the volume of problems derived from this approach is very extensive.

Founded in 2016, Pimloc has built deep learning systems for security video and diverse image collections. The technology helps organisations (both private and public) to manage security footage and protect sensitive visual data (according to GDPR) -- and also protect the rights of whoever finds themselves on camera. "The protection of personal data needs to be designed into visual security and analytics systems by default to protect individuals from the misuse of face recognition and other technologies," says CEO Simon Randall. Specifically, the startup's products include Pholio, a search and discovery platform for large image and video collections and live streams, and Secure Redact, a data privacy platform for the anonymisation of personal data in video. They're currently used in a range of sectors including mobility, insurance, entertainment, broadcasting and law enforcement.

It has only been 8 years since the modern era of deep learning began at the 2012 ImageNet competition. Progress in the field since then has been breathtaking and relentless. If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.

Many companies including: OpenAI, Google/DeepMind, Microsoft, and countless others, have started the race for "truly" intelligent AI. For the majority of this article I'll be referencing OpenAI's GPT series of machine learning models. However, the question: "what does it mean to be truly intelligent?" OpenAI have modeled this problem as a text transformer model. This model takes sequences of pieces of words (two character pairs) and tries to predict the next set of word parts.

Google Data Studio (GDS) is a free dashboard and reporting tool (which lives in the cloud). It allows you to create dynamic, collaborative reports, and visualization dashboards. Paid Business Intelligence and Data Analytics Tools Like Tableau Are have either plateaued or will plateau soon. Many of these are either too expensive for small or teams or have a steep learning curve for beginners. This course helps you start with GDS and become proficient in producing powerful visualizations and reports.4.5/5

About: This project utilises deep learning models, Long-Short Term Memory (LSTM) and neural network algorithm, to predict stock prices.

When working with deep learning models, I have often found myself in a peculiar situation when there is not much data to train my model. It was in times like these when I came across the concept of image augmentation. The image augmentation technique is a great way to expand the size of your dataset. You can come up with new transformed images from your original dataset. But many people use the conservative way of augmenting the images i.e. augmenting images and storing them in a numpy array or in a folder.