Deep Learning, NLP, NMT, AI, ML
Introduction Deep Learning is a very rampant field right now – with so many applications coming out day by day. And the best way to get deeper into Deep Learning is to get hands-on with it. Take up as much projects as you can, and try to do them on your own. This would help you grasp the topics in more depth and assist you in becoming a better Deep Learning practitioner. In this article, we will take a look […]
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Introduction “If you talk to a man in a language he understands, that goes to his head. If you talk to him in his own language, that goes to his heart.” – Nelson Mandela The beauty of language transcends boundaries and cultures. Learning a language other than our mother tongue is a huge advantage. But the path to bilingualism, or multilingualism, can often be a long, never-ending one. There are so many little nuances that we get lost in the […]
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Introduction It is not the strongest or the most intelligent who will survive but those who can best manage change. Evolution is the only way anything can survive in this universe. And when it comes to industry relevant education in a fast evolving domain like Machine Learning and Artificial Intelligence – it is necessary to evolve or you will simply perish (over time). I have personally experienced this first hand while building Analytics Vidhya. It still amazes me to see […]
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Overview Learn how to build your own text generator in Python using OpenAI’s GPT-2 framework GPT-2 is a state-of-the-art NLP framework – a truly incredible breakthrough We will learn how it works and then implements our own text generator using GPT-2 Introduction “The world’s best economies are directly linked to a culture of encouragement and positive feedback.” Can you guess who said that? It wasn’t a President or Prime Minister. It certainly wasn’t a leading economist like Raghuram Rajan. […]
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Overview Here are six open-source data science projects to enhance your skillset These projects cover a diverse set of domains, from computer vision to natural language processing (NLP), among others Pick your favorite open-source data science project(s) and get coding! Introduction I recently helped out in a round of interviews for an open data scientist position. As you can imagine, there were candidates from all kinds of backgrounds – software engineering, learning and development, finance, marketing, etc. What stood […]
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Introduction spaCy is my go-to library for Natural Language Processing (NLP) tasks. I’d venture to say that’s the case for the majority of NLP experts out there! Among the plethora of NLP libraries these days, spaCy really does stand out on its own. If you’ve used spaCy for NLP, you’ll know exactly what I’m talking about. And if you’re new to the power of spaCy, you’re about to be enthralled by how multi-functional and flexible this library is. The factors […]
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For a second, let’s focus solely on the teacher. If we continuing the path past the MHA-block, things remain the same compared to a vanilla transformer block until we reach the second “Add & Norm” operation. After this layer, we have a bottleneck transform, this time to reduce the dimension back to that of the input. This allows us to perform another Add & Norm operation with the transformer block input before feeding the result onto the next block. Stacked […]
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This article was published as a part of the Data Science Blogathon. Introduction This article is in continuation of my previous article on using Machine learning in Support environments. I shared my views on, how using simple python code we can enrich our call centers/support division activities in our own organization or customer organization. In that article, I shared an insight into what and how we can make a difference to the current environment using ML in giving better service […]
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Deep speaker embeddings have become the leading method for encoding speaker identity in speaker recognition tasks. The embedding space should ideally capture the variations between all possible speakers, encoding the multiple aspects that make up speaker identity… In this work, utilizing speaker age as an auxiliary variable in US Supreme Court recordings and speaker nationality with VoxCeleb, we show that by leveraging additional speaker attribute information in a multi task learning setting, deep speaker embedding performance can be increased for […]
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Deep learning is slowly, but steadily, hitting a memory bottleneck. While the tensor computation in top-of-the-line GPUs increased by 32x over the last five years, the total available memory only grew by 2.5x… This prevents researchers from exploring larger architectures, as training large networks requires more memory for storing intermediate outputs. In this paper, we present MONeT, an automatic framework that minimizes both the memory footprint and computational overhead of deep networks. MONeT jointly optimizes the checkpointing schedule and the […]
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