Kaggle cli download specific file
Cloud project. Contribute to IshwarBhat/spark-twitter development by creating an account on GitHub. My solution to Google Brain's Tensorflow Speech Recognition challenge on Kaggle - mateuszjurewicz/tensorflow_speech_recognition Content for Udacity's Machine Learning curriculum. Contribute to jo4x962k7JL/udacity_MLND development by creating an account on GitHub. Make a map of air quality measurements in Madrid using Leaflet and the XYZ API. Slides for my tutorial at Oscon 2012 http://goo.gl/fpxVE The best known booru, with a focus on quality, is Danbooru. We create & provide a torrent which contains ~2.5tb of 3.33m images with 92.7m tag instances (of 365k defined tags, ~27.8/image) covering Danbooru from 24 May 2005 through 31… Check out Blog from TekStreamFunctional Map of the World Challengehttps://iarpa.gov/challenges/fmow.htmlThe dataset contains satellite-specific metadata that researchers can exploit to build a competitive algorithm that classifies facility, building, and land use.
Ingestion of bid requests through Amazon Kinesis Firehose and Kinesis Data Analytics. Data lake storage with Amazon S3. Restitution with Amazon QuickSight and CloudWatch. - hervenivon/aws-experiments-data-ingestion-and-analytics
Content for Udacity's Machine Learning curriculum. Contribute to jo4x962k7JL/udacity_MLND development by creating an account on GitHub. Make a map of air quality measurements in Madrid using Leaflet and the XYZ API. Slides for my tutorial at Oscon 2012 http://goo.gl/fpxVE
What you'll learn. How to upload data to Kaggle using the API; (Optional) how to document your dataset and make it public; How to update an existing dataset
Choices are most often based on team experience, vendor relationships, and an enterprise’s specific business use cases. Deep learning convolutional neural network by tensorflow python, complete and easy understanding Data repository for pretrained NLP models and NLP corpora. - RaRe-Technologies/gensim-data AIBench, a tool for comparing and evaluating AI serving solutions. forked from [tsbs](https://github.com/timescale/tsbs) and adapted to AI serving use case - RedisAI/aibench A curated list of NLP resources focused on BERT, attention mechanism, Transformer networks, and transfer learning. - cedrickchee/awesome-bert-nlp
Cloud project. Contribute to IshwarBhat/spark-twitter development by creating an account on GitHub.
Both the input and output data can be fetched and stored in different locations, such as a database, a stream, a file, etc. The transformation stages are usually defined in code, although some ETL tools allow you to represent them in a… Table columns will hold some property (or properties) of the above concepts - some will hold amounts, some will hold information regarding the recipient etc. As the exact nature of each of these concepts varies greatly by context, the… This property Should correspond to the name of field/column in the data file (if it has a name). As such it Should be unique (though it is possible, but very bad practice, for the data file to have multiple columns with the same name). Implementation of Model serving in pipelines. Contribute to lightbend/pipelines-model-serving development by creating an account on GitHub. explain transfer learning and visualization. Contribute to georgeAccnt-GH/transfer_learning development by creating an account on GitHub.
Official API for https://www.kaggle.com, accessible using a command line tool This will trigger the download of kaggle.json , a file containing your API credentials. and 'large' --file-type FILE_TYPE Search for datasets with a specific file type.
Blockchains are distributed blocks of data linked together by a specific set of consensus protocols, while cryptocurrencies are the tokens used to access services and applications built on the blockchains in questions.Setting Up Python for Machine Learning on Windows – Real Pythonhttps://realpython.com/python-windows-machine-learning-setupIn this step-by-step tutorial, you’ll cover the basics of setting up a Python numerical computation environment for machine learning on a Windows machine using the Anaconda Python distribution. step: name: Run-dl4j-mnist-single-layer-train-model image: neomatrix369/dl4j-mnist-single-layer:v0.5 command: - echo "~~~ Unpack the MNist dataset into ${HOME} folder" - tar xvzf ${VH_Inputs_DIR}/dataset/mlp-mnist-dataset.tgz -C ${HOME…