Popular Blogs

Building a Neural Net to Visualize High-Dimensional Data in TensorFlow

Word embeddings and high-dimensional data are ubiquitous in many facets of deep learning research such as natural language processing, building recommendation systems. Google in the recent times has open sourced the embedding project that works as an interactive collaborative visualization tool to visualize the high-dimensional data.  The embedding works as a navigational map from the points to the data inputs in Euclidean space.  Many types of big data require visualizatio...

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Installation Guide for TensorFlow on macOS High Sierra 10.13.4 for your DeepLearning w/ Java, C, and Go

This installation particularly focuses on macOS High Sierra version 10.13.4. It’s likely that the installation may work on previous version of macOS High Sierra. However, addressing the issues related to previous versions is not considered in this topic.  There are several options to install TensorFlow on macOS. Docker Native Pip Virtual Python environment Installation of TensorFlow with Anaconda Installation of TensorFlow for JDK Installation of Tensor...

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3 Ways to Apply Latent Semantic Analysis on Large-Corpus Text on macOS Terminal, JupyterLab, and Colab

Latent semantic analysis works on large-scale datasets to generate representations to discover the insights through natural language processing. There are different approaches to perform the latent semantic analysis at multiple levels such as document level, phrase level, and sentence level. Primarily semantic analysis can be summarized into lexical semantics and the study of combining individual words into paragraphs or sentences. The lexical semantics classifies and decompo...

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AI Trained to Perform Sentiment Analysis on Amazon Electronics Reviews in JupyterLab

The recent advancements in natural language processing over last few decades allowed a significant number of enterprises to leverage the potential of sentiment analysis by training artificial intelligence through deep learning and machine learning algorithms to teach the machine and perform particular operations similar to what humans apply through cognitive abilities. Though, the machines cannot comprehend, perceive, and process the scenarios through life-like experience, ad...

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Building SMS SPAM Detector and Generating a WordCloud with Kaggle Dataset in JupyterLab

Background problem At least 97% of American use text messages over mobile phones every day. In 2016, according to the research conducted by Portio research, 8.3 trillion messages exchanged over the mobile phones. The rising flood of big data shows an exchange of 23 billion messages per day and 16 million messages per minute. There are around 6.4 billion mobile subscribers around the world by the end of 2012. According to Portio Research, there will be a CAGR growth of 4.8% o...

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