A brief history: ImageNet was first published in 2009 and over the next four years would go on to form the bedrock of most computer vision models. To this day whether you are training a model to detect pneumonia or classify models of cars you will probably start with a model pre-trained on ImageNet or some other large (and general image) dataset. More recently papers … [Read more...] about Transfer Learning for Time Series Forecasting and Classification
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Graph Convolutional Networks (GCN)
In this post, we’re gonna take a close look at one of the well-known graph neural networks named Graph Convolutional Network (GCN). First, we’ll get the intuition to see how it works, then we’ll go deeper into the maths behind it. Why Graphs? Many problems are graphs in true nature. In our world, we see many data are graphs, such as molecules, social … [Read more...] about Graph Convolutional Networks (GCN)
The Essential Landscape of Enterprise AI Companies (2020)
By our definition, "enterprise" technology companies create tools for workplace roles and functions that a large number of businesses use. Plenty of enterprise companies use combinations of automated data science, machine learning, and modern deep learning approaches for tasks like data preparation, predictive analytics, and process automation. Many are well-established … [Read more...] about The Essential Landscape of Enterprise AI Companies (2020)
These 10 Companies Are Transforming Marketing With AI
Traditional marketing tools lack the flexibility, scalability, and comprehensiveness to address many of the challenges faced by modern companies. With growing digitization and an always-online audience, more marketing teams now require artificial intelligence (AI) to stay competitive. Before rushing to hire a data science team, you need to evaluate the third-party AI … [Read more...] about These 10 Companies Are Transforming Marketing With AI
Reformer, Longformer, and ELECTRA: Key Updates To Transformer Architecture In 2020
The leading pre-trained language models demonstrate remarkable performance on different NLP tasks, making them a much-welcomed tool for a number of applications, including sentiment analysis, chatbots, text summarization, and so on. However, good performance usually comes at the cost of enormous computational resources that are not accessible by most researchers and business … [Read more...] about Reformer, Longformer, and ELECTRA: Key Updates To Transformer Architecture In 2020
Deep Transfer Learning for Image Classification
The following tutorial covers how to set up a state of the art deep learning model for image classification. The approach is based on the machine learning frameworks “Tensorflow” and “Keras”, and includes all the code needed to replicate the results in this tutorial. The prerequisites for setting up the model is access to labelled data, and as an example case I have used … [Read more...] about Deep Transfer Learning for Image Classification
5 Ways To Leverage AI Research In Marketing & Advertising
Today, Artificial Intelligence (AI) can drive effective solutions to lots of marketing challenges. It can help you optimize your advertising budget, personalize your customers’ experience, suggest the most accurate attribution model, boost your marketing analytics, and even generate original brand content, including images and advertising slogans. However, AI is evolving so … [Read more...] about 5 Ways To Leverage AI Research In Marketing & Advertising
AI For Portfolio Management: From Markowitz To Reinforcement Learning
Artificial intelligence, machine learning, big data, and other buzzwords are disrupting decision making in almost any area of finance. On the back office, machine learning is widely applied to spot anomalies in execution logs, for risk management and fraudulent transaction detection. At the front office, AI is used for customer segmentation and support and pricing the … [Read more...] about AI For Portfolio Management: From Markowitz To Reinforcement Learning
Data Labeling For Natural Language Processing
Why Does Training Data Matter? Machine Learning has made significant strides in the last decade. This can be attributed to parallel improvements in processing power and new breakthroughs in Deep Learning research. Another key reason is the abundance of data that has been accumulated. Analysts estimate humankind sits atop 44 zettabytes of information today. The … [Read more...] about Data Labeling For Natural Language Processing
The 5 Components Towards Building Production-Ready Machine Learning Systems
Introduction The biggest issue facing machine learning is how to put the system into production. Machine learning systems differ from traditional software in two fundamental ways: Machine learning is never fully deterministic; therefore, the performance of an ML system can’t be evaluated against a strict specification. Instead, it should always be evaluated against … [Read more...] about The 5 Components Towards Building Production-Ready Machine Learning Systems