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Introducing Comet.ml’s Python API Client
Programmatically access your machine learning system of record Accessing your model weights, metrics, hyperparameters, images, and other workflow artifacts should be easy for 10 or 10,000 experiments. Our new Python API client allows you to...
Comet.ml cheat sheet: supercharge your machine learning experiment management
Comet.ml allows you to automatically track your machine learning code, experiments, hyperparameters, and results to achieve reproducibility, transparency, and more efficient iteration cycles. We built it after seeing many data scientists trying to grapple...
A Year in Review: NYC AI & Machine Learning meetups
Our experience hosting New York data scientists and researchers from academia and industry 2018 has been an excellent year for machine learning breakthroughs and the larger data science community! Our team at Comet.ml began hosting...
Implementing ResNet with MXNET Gluon and Comet.ml for image classification
In this tutorial, we will illustrate how to build an image recognition model using a convolutional neural network (CNN) implemented in MXNet Gluon, and integrate Comet.ml for experiment tracking and monitoring. We will be...
Real-time numbers recognition (MNIST) on an iPhone with CoreML from A to Z
Learn how to build and train a deep learning network to recognize numbers (MNIST), how to convert it in the CoreML format to then deploy it on your iPhoneX and make it recognize numbers...
Monitoring machine learning model results live from Jupyter notebooks
Tracking and saving your model results just got that much easier with Comet.ml For many data scientists, Jupyter notebooks have become the tool of choice. Its ability to combine software code, computational output, explanatory text,...
Real-world examples of applied machine learning from AI Conference
See how companies like Uber and ZocDoc use machine learning to improve key business metrics The majority of buzz around machine learning and AI focuses on things like computerized play of Dota or realistic speech...
Introducing Comet.ml Project Visualizations
Compare across your model iterations efficiently with rich visualizations to identify your champion model At Comet.ml, we believe that machine learning should be highly iterative, collaborative, and reproducible. Comet.ml allows data science teams to automatically...
Part II: Manual Feature Engineering techniques for the Kaggle Home Credit Default Competition
Our second post in this series, where the Comet.ml team competes to win the Kaggle Home Credit Default Competition! This post is the second in our series as we work through our submission for...
Podcast Take: In Context Episode 9 with StitchFix’s Chief Algorithms Officer
The latest episode of the In Context podcast is a must-listen for anyone in the machine learning space. In Context’s host, Kathryn Hume from integrate.ai, always asks a perfect balance of business and technical...
Introducing Comet.ml’s new Query Builder
Now you can easily find and organize your experiments with filtered views based on experiment metrics, metadata, and parameters...
Aug 3, 2018
1 min read
Real-time model performance visualizations with Comet.ml
At Comet.ml, we strive to help data scientists and machine learning engineers speed up the development and productionisation of...
Jun 28, 2018
1 min read
Comet.ml: supercharging your machine learning workflow
I’m very excited to announce that I’ve joined Comet.ml as Product Lead! After graduation, I became a product manager...
May 18, 2018
1 min read
Building reliable machine learning models with cross-validation
Cross-validation is a technique used to measure and evaluate machine learning models performance. During training we create a number of partitions of the training...
Aug 6, 2018
2 min read
Part I: Conducting Exploratory Data Analysis (EDA) for the…
Follow along as the Comet.ml team competes to win the Kaggle Home Credit Default Competition — this is the first of a series of posts on...
Jul 13, 2018
4 min read
A Data Scientist’s Guide to Communicating Results
So your model is finally done running, you’ve tweaked and optimized all of the hyperparameters you could to obtain the best results, and you’re...
Jul 10, 2018
3 min read
Deep Learning: Theory & Practice
This post by Yoel Zeldes is originally from his blog Another Datum and was reposted with his permission. Yoel is an algorithm engineer at...
Jun 18, 2018
7 min read
Using fastText and Comet.ml to classify relationships in Knowledge…
TLDR: In this post, we will examine how a simple model, fastText, learns to represent entities in a subset of the FB15K knowledge graph,...
Jun 18, 2018
6 min read
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