- ColabCode: Deploying Machine Learning Models From Google Colab - Jul 22, 2021.
New to ColabCode? Learn how to use it to start a VS Code Server, Jupyter Lab, or FastAPI.
- Add A New Dimension To Your Photos Using Python - Jun 28, 2021.
Read this to learn how to breathe new life into your photos with a 3D Ken Burns Effect.
- Must-have Chrome Extensions For Machine Learning Engineers And Data Scientists - May 11, 2021.
Browser extensions are a productivity secret weapon for hackers and developers. Many machine learning practitioners use Chrome, and this list features must-have Chrome extensions for machine learning engineers and data scientists that you should check out today.
- Multilingual CLIP with Huggingface + PyTorch Lightning - Mar 26, 2021.
An overview of training OpenAI's CLIP on Google Colab.
- Building Neural Networks with PyTorch in Google Colab - Oct 30, 2020.
Combining PyTorch and Google's cloud-based Colab notebook environment can be a good solution for building neural networks with free access to GPUs. This article demonstrates how to do just that.
- The NLP Model Forge: Generate Model Code On Demand - Aug 24, 2020.
You've seen their Big Bad NLP Database and The Super Duper NLP Repo. Now Quantum Stat is back with its most ambitious NLP product yet: The NLP Model Forge.
- Top Google AI, Machine Learning Tools for Everyone - Aug 18, 2020.
Google is much more than a search company. Learn about all the tools they are developing to help turn your ideas into reality through Google AI.
- A Complete guide to Google Colab for Deep Learning - Jun 16, 2020.
Google Colab is a widely popular cloud service for machine learning that features free access to GPU and TPU computing. Follow this detailed guide to help you get up and running fast to develop your next deep learning algorithms with Colab.
- The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks - Apr 24, 2020.
Check out this repository of more than 100 freely-accessible NLP notebooks, curated from around the internet, and ready to launch in Colab with a single click.
- TensorFlow Dev Summit 2020: Top 10 Tricks for TensorFlow and Google Colab Users - Apr 8, 2020.
In this piece, we’ll highlight some of the tips and tricks mentioned during this year’s TF summit. Specifically, these tips will help you in getting the best out of Google’s Colab.
- The 4 Best Jupyter Notebook Environments for Deep Learning - Mar 19, 2020.
Many cloud providers, and other third-party services, see the value of a Jupyter notebook environment which is why many companies now offer cloud hosted notebooks that are hosted on the cloud. Let's have a look at 3 such environments.
- 5 Google Colaboratory Tips - Mar 2, 2020.
Are you looking for some tips for using Google Colab for your projects? This article presents five you may find useful.
- Pytorch Cheat Sheet for Beginners and Udacity Deep Learning Nanodegree - Aug 2, 2019.
This cheatsheet should be easier to digest than the official documentation and should be a transitional tool to get students and beginners to get started reading documentations soon.
- Mastering Fast Gradient Boosting on Google Colaboratory with free GPU - Mar 19, 2019.
CatBoost is a fast implementation of GBDT with GPU support out-of-the-box. Google Colaboratory is a very useful tool with free GPU support.
- How to Train a Keras Model 20x Faster with a TPU for Free - Mar 19, 2019.
This post shows how to train an LSTM Model using Keras and Google CoLaboratory with TPUs to exponentially reduce training time compared to a GPU on your local machine.
- 3 More Google Colab Environment Management Tips - Jan 2, 2019.
This is a short collection of lessons learned using Colab as my main coding learning environment for the past few months. Some tricks are Colab specific, others as general Jupyter tips, and still more are filesystem related, but all have proven useful for me.
- Keras Hyperparameter Tuning in Google Colab Using Hyperas - Dec 12, 2018.
In this post, I will show you how you can tune the hyperparameters of your existing keras models using Hyperas and run everything in a Google Colab Notebook.
- Creating a simple text classifier using Google CoLaboratory - Mar 15, 2018.
Google CoLaboratory is Google’s latest contribution to AI, wherein users can code in Python using a Chrome browser in a Jupyter-like environment. In this article I have shared a method, and code, to create a simple binary text classifier using Scikit Learn within Google CoLaboratory environment.
- Top KDnuggets tweets, Mar 7-13: #MachineLearning Algorithms: Which One to Choose for Your Problem; Train Your ML Models on Google GPUs for Free - Mar 15, 2018.
Also Introduction to Markov Chains; 18 Inspiring Women In #AI, #Analytics #BigData, #DataScience, #MachineLearning.
- 5 Things to Know About Machine Learning - Mar 7, 2018.
This post will point out 5 thing to know about machine learning, 5 things which you may not know, may not have been aware of, or may have once known and now forgotten.
- Deep Learning Development with Google Colab, TensorFlow, Keras & PyTorch - Feb 20, 2018.
Now you can develop deep learning applications with Google Colaboratory - on the free Tesla K80 GPU - using Keras, Tensorflow and PyTorch.
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- KDnuggets™ News 18:n07, Feb 14: 5 Machine Learning Projects You Should Not Overlook; Intro to Python Ensembles - Feb 14, 2018.
5 Machine Learning Projects You Should Not Overlook; Introduction to Python Ensembles; Which Machine Learning Algorithm be used in year 2118?; Fast.ai Lesson 1 on Google Colab (Free GPU)
- 3 Essential Google Colaboratory Tips & Tricks - Feb 12, 2018.
Google Colaboratory is a promising machine learning research platform. Here are 3 tips to simplify its usage and facilitate using a GPU, installing libraries, and uploading data files.
- Fast.ai Lesson 1 on Google Colab (Free GPU) - Feb 8, 2018.
In this post, I will demonstrate how to use Google Colab for fastai. You can use GPU as a backend for free for 12 hours at a time. GPU compute for free? Are you kidding me?
- CoLaboratory: Doing Data Science Collaboratively Like Google Doc - Sep 3, 2014.
A review of CoLaboratory which enables data scientists to write code like on Google Doc.