Author: Deep Learner

Analysis

A tool for the analysis and visualization of spatial molecular data

Squidpy – Spatial Single Cell Analysis in Python Squidpy is a tool for the analysis and visualization of spatial molecular data. It builds on top of scanpy and anndata, from which it inherits modularity and scalability. It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available. Manuscript Please see our preprint on bioRxiv to learn more. Squidpy’s key applications Build and analyze the neighborhood graph from spatial coordinates. Compute spatial statistics […]

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Advanced, Artificial intelligence, conversational AI, Machine Learning, NLP, Unstructured Data, Unsupervised

Let’s Understand How does a chatbot work ?

Introduction A technology that makes the interaction between humans and machines in natural language possible, is an Artificial Intelligence Chatbot! They act like a typical search engine but with more enhanced features. Applications of Artificial Intelligence Chatbots are spread over various domains including eCommerce, healthcare, education, travel, automation, finance, hospitality, insurance, and so on. The chatbots are domain-specific and do what they are intended for.  The applications in their domain include: answering customer queries, booking services like flights, movie tickets, […]

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Serverless

A toolkit for developing and deploying serverless Python code in AWS Lambda

Python-lambda Python-lambda is a toolset for developing and deploying serverless Python code in AWS Lambda. With python-lambda and pytube both continuing to gain momentum, I’m calling for contributors to help build out new features, review pull requests, fix bugs, and maintain overall code quality. If you’re interested, please email me at nficano[at]gmail.com. AWS Lambda is a service that allows you to write Python, Java, or Node.js code that gets executed in response to events like http requests or files uploaded […]

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Graph

A library that identifies subgraphs or motifs in a large graph

dotmotif DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like this: # Look for all motifs of the form, # Neuron A excites B: A -> B [type = “excitatory”] # …and B inhibits C: B -> C [type = “inhibitory”] Or like this: TwitterInfluencer(person) { # An influencer has more than a million # followers and is verified. person.followers > 1000000 person.verified = true } InfluencerAwkward(person1, person2) { # Two people who […]

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PDF

Python utility library for compositing PDF documents with reportlab

pdfdoc-py Python utility library for compositing PDF documents with reportlab. Installation The pdfdoc-py package can be installed directly from the source code: $ git clone https://github.com/michaelgale/pdfdoc-py.git $ cd pdfdoc-py $ python setup.py install Usage After installation, the package can imported: $ python >>> import pdfdoc >>> pdfdoc.__version__ Example of making a label sheet with 25 labels on Avery 5262 self-adhesive label sheets: from pdfdoc import * ld = LabelDoc(“my_labels.pdf”, style=AVERY_5262_LABEL_DOC_STYLE) labels = [i for i in range(25)] for label, row, […]

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Visualization

A Python library for processing and visualization of trajectories and other spatial-temporal data

PyMove PyMove is a Python library for processing and visualization of trajectories and other spatial-temporal data. Main Features PyMove proposes: A familiar and similar syntax to Pandas; Clear documentation; Extensibility, since you can implement your main data structure by manipulating other data structures such as Dask DataFrame, numpy arrays, etc., in addition to adding new modules; Flexibility, as the user can switch between different data structures; Operations for data preprocessing, pattern mining and data visualization. Creating a Virtual Environment It […]

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Search

Generate custom detailed survey paper with topic clustered sections and proper citations

Auto-Research A no-code utility to generate a detailed well-cited survey with topic clustered sections (draft paper format) and other interesting artifacts from a single research query. Data Provider: arXiv Open Archive Initiative OAI Requires: python 3.7 or above poppler-utils list of requirements in requirements.txt 8GB disk space 13GB CUDA(GPU) memory – for a survey of 100 searched papers(max_search) and 25 selected papers(num_papers) Demo : Video Demo : https://drive.google.com/file/d/1-77J2L10lsW-bFDOGdTaPzSr_utY743g/view?usp=sharing Kaggle Re-usable Demo : https://www.kaggle.com/sidharthpal/auto-research-generate-survey-from-query ([TIP] click ‘edit and run’ to run […]

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Deep Learning

A library for preparing and evaluating scalable deep learning hybrid recommender systems

collie A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch. Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie dog breed. Collie offers a collection of simple APIs for preparing and splitting datasets, incorporating item metadata directly into a model architecture or loss, efficiently evaluating a model’s performance on the GPU, and so much more. Above all else though, Collie is built with […]

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