September 29, 2020 Advanced, NLP, Project, Python, Ranking, Technique, Text, Unstructured Data, Word Embeddings Leave a comment

Information Retrieval using word2vec based Vector Space Model

Overview Learn about Information Retrieval (IR), Vector Space Models (VSM), and Mean Average Precision (MAP) Create a project on Information Retrieval using word2vec based Vector Space Model Introduction “Google it!”- Isn’t it something we say every day? Whenever we come across something that we don’t know about, we “Google it.” Google Search is a great tool that can be used for even finding a needle from a haystack. This generation absolutely relies on Google for answers to all kinds […]

September 27, 2020 Advanced, Algorithm, Technique Leave a comment

How to Rank Entities with Multi-Criteria Decision Making Methods(MCDM)

Ranking with MCDM You can’t rest on your #1 ranking-because the guy at #2 isn’t resting. He’s still improving his site — Ryan Jones We all come across different multi-criteria decision-making problems in our day to day life. Example — Shopping: Which one product should I buy out of X candidate products? Ranking problems are the most interesting problems a data To finish reading, please visit source site

September 25, 2020 Advanced

Characteristics of Good Visual Analytics and Data Discovery Tools

Visual Analytics and Data Discovery allow analysis of big data sets to find insights and valuable information. This is much more than just classical Business Intelligence (BI). See this article for more details and motivation: “Using Visual Analytics to Make Better Decisions: the Death Pill Exa…“. Let’s take a look at important characteristics to choose the right tool for your use cases. Visual Analytics Tool Comparison and Evaluation Several tools are available on the market for Visual Analytics and Data […]

September 23, 2020 Advanced, Computer Vision, Deep Learning, Python, Technique, Unstructured Data Leave a comment

A Detailed Study of Self Supervised Contrastive Loss and Supervised Contrastive Loss

Introduction Supervised Contrastive Learning paper claims a big deal about supervised learning and cross-entropy loss vs supervised contrastive loss for better image representation and classification tasks. Let’s go in-depth in this paper what is about. Claim actually close to 1% improvement on image net data set¹. Architecture wise, its a very simple network resnet 50 having a 128-dimensional head. If you want you can add a few more layers as well. Architecture and training process from the paper Codeself.encoder = […]

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