✨📒 Did you know that you can connect to GoogleColab using a local runtime, or a virtual machine running in the cloud (AWSCloud, GoogleCloud, Azure, etc.)? 👉 Check out our guide + blogpost for how to set up your environment: https://research.google.com/colaboratory/local-runtimes.html … https://blog.kovalevskyi.com/gce-deeplearning-images-as-a-backend-for-google-colaboratory-bc4903d24947


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Stanford Tracking Artificial Intelligence Research To See Future - Palo Alto, CA Patch

Read more here: https://ift.tt/2PCc1JY

#ArtificialIntelligence #AI #DataScience #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT


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linux
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What's the hardest part of ML? The most expensive? The most time-consuming? Choosing from:
- data collection & labelling
- data cleaning
- modelling / science
- implementation
- infrastructure / cloud SysOps
- deployment
- maintenance

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Attention Networks with Keras The "Attention Network" is one of the most interesting advancements in natural language processing. So, what makes an attention network tick & why it's special?

https://buff.ly/2LNaK0K

#NLP #NeuralNetworks #AI

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hardest: features and parameters of the model, most expensive: data collection, cleaning and labeling, most time consuming: multiple iterations in order to converge to the optimal parameters, testing & evaluation.

Dr François Chollet

This is a great answer and I agree -- modelling/science is the hardest (if you want to do it right), and also the most time-consuming due to lengthy iterations. Meanwhile data collection and labelling is the most expensive, and often the most important to the success of a project.

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"A Brief Introduction to Machine Learning for Engineers"

By Osvaldo Simeone: https://lnkd.in/eT9FVYd

#ArtificialIntelligence #MachineLearning #NeuralNetworks


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A Full Hardware Guide to Deep Learning

By Tim Dettmers: https://lnkd.in/emiGW6p

#ai #deeplearning #gpu #gpus #hardware


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Playing first-person shooter games with webcam and #DeepLearning (Tensorflow #ObjectDetection)

Find out how you can use an object detection model to control and play any first-person shooter game with your computer's webcam. Links to the code below.

Full Video: https://lnkd.in/eBq7z4r

Blog: https://lnkd.in/eekrqWk

Code: https://lnkd.in/ekhwwiJ

Subscribe: youtube.com/c/DeepGamingAI

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Want to learn ML through code examples?

Check out these 5 scikit-learn tutorials to get started:

1. Randomized search vs grid search - https://lnkd.in/gjHpjJK

2. Using regularization to improve your GBM models - https://lnkd.in/gYNCNGD

3. Selecting the correct number of estimators for GBM models - https://lnkd.in/gW5AQTk

4. Selecting the correct number of estimators for random forest models - https://lnkd.in/ge66wUH

5. Decision boundary comparison for popular classifier models (check out this viz!) - https://lnkd.in/gHVg9nm

There are a ton more that you can go through on the sk-learn tutorial page as well.

👉 Check them out here - https://lnkd.in/gAv3hq7

👉 If you need more help learning machine learning or getting a job as a data scientist, then hop on my email list and I'd be happy to help - https://lnkd.in/g7AYg72

#datascience #machinelearning

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A simple notebook to remove the background of objects using Mask R-CNN

By Zaid Alyafeai: https://lnkd.in/exr7yWi

#artificialinteligence #deeplearning #machinelearning #tensorflow

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Ten Simple Rules for Reproducible Research in Jupyter Notebooks

Rule et al.: https://lnkd.in/efWmkyi

#BigData #ComputerScience #DataScience #MachineLearning

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Tuning Machine Learning Hyperparameters

https://heartbeat.fritz.ai/tuning-machine-learning-hyperparameters-40265a35c9b8

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if you're going to start a #ML services startup, make it about data collection and labelling. This is main pain point, and where the most value can be unlocked.

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A Concise Handbook of TensorFlow (https://tf.wiki ) Online book for those who already knows #ML / #DL theories and want to focus on learning #TensorFlow itself

https://tf.wiki/en/preface.html

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The International Conference on #Probabilistic Programming Talks from the #PROBPROG 2018 #Conference, held at the MIT Media Lab in Cambridge

https://www.youtube.com/playlist?list=PL_PW0E_Tf2qvXBEpl10Y39RULTN-ExzZQ



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rlkit – Reinforcement learning framework and algorithms implemented in #PyTorch

https://github.com/vitchyr/rlkit

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videos of #NeurIPS2018 invited talks: https://videos.videoken.com/index.php/videoscategory/neurips-2018/ … videos of more sessions here: https://www.facebook.com/pg/nipsfoundation/videos

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How to Clone a Partition or Hard drive in #Linux https://www.tecmint.com/clone-linux-partitions/

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