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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
@AI_Python
π£ @AI_Python_arXiv
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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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π£ @AI_Python_arXiv
β΄οΈ @AI_Python_EN
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.
π Check them out here - https://lnkd.in/gAv3hq7
π 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
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_Arxiv
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.
π Check them out here - https://lnkd.in/gAv3hq7
π 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
β΄οΈ @AI_Python_EN
βοΈ @AI_Python
π£ @AI_Python_Arxiv
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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π£ @AI_Python_Arxiv
By Zaid Alyafeai: https://lnkd.in/exr7yWi
#artificialinteligence #deeplearning #machinelearning #tensorflow
β΄οΈ @AI_Python_EN
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π£ @AI_Python_Arxiv
Ten Simple Rules for Reproducible Research in Jupyter Notebooks
Rule et al.: https://lnkd.in/efWmkyi
#BigData #ComputerScience #DataScience #MachineLearning
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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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https://heartbeat.fritz.ai/tuning-machine-learning-hyperparameters-40265a35c9b8
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AI, Python, Cognitive Neuroscience
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 FranΓ§ois Chollet This is a great answerβ¦
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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π£ @AI_Python_arXiv
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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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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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π£ @AI_Python_arXiv
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https://www.youtube.com/playlist?list=PL_PW0E_Tf2qvXBEpl10Y39RULTN-ExzZQ
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β΄οΈ @AI_Python
rlkit β Reinforcement learning framework and algorithms implemented in #PyTorch
https://github.com/vitchyr/rlkit
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https://github.com/vitchyr/rlkit
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videos of #NeurIPS2018 invited talks: https://videos.videoken.com/index.php/videoscategory/neurips-2018/ β¦ 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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Interested in research on the interface of #evolution, systems and molecular #biology, #mathematics, and #statistics? Apply now to join the Evolutionary Dynamics lab IGCiencia as a postdoc, programmer, or PhD student! https://evoldynamics.org/positions Please spread the word!
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share white paper on Dopamine, #RL framework. got lots of positive feedback at #NeurIPS2018 ,
https://arxiv.org/abs/1812.06110 https://github.com/google/dopamine
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https://arxiv.org/abs/1812.06110 https://github.com/google/dopamine
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#Programming
π It is a painful thing, to look at your own trouble and know that you yourself and no one else has made it. ~Sophocles Debugging #software includes:
πControl flow analysis
πUnit | integration testing
πLog file analysis
πMonitoring
πMemory dumps
πProfiling
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π It is a painful thing, to look at your own trouble and know that you yourself and no one else has made it. ~Sophocles Debugging #software includes:
πControl flow analysis
πUnit | integration testing
πLog file analysis
πMonitoring
πMemory dumps
πProfiling
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
3 reasons why #Coding (specifically, #Python) Should Become Your Official Corporate Language:
1)Teaches to think and solve problems.
2)Teaches the principles of Open-Source.
3)Teaches to work collaboratively.
https://bit.ly/2z3Qp2A #abdsc #DataScience #DataScientists
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1)Teaches to think and solve problems.
2)Teaches the principles of Open-Source.
3)Teaches to work collaboratively.
https://bit.ly/2z3Qp2A #abdsc #DataScience #DataScientists
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
Copying an element from a photo and pasting it into a painting. Main idea is a modification of the VGG style transfer technique. Fun results.
Paper:
https://arxiv.org/pdf/1804.03189v3.pdf
Code:
https://github.com/luanfujun/deep-painterly-harmonization
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π£ @AI_Python_arXiv
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Paper:
https://arxiv.org/pdf/1804.03189v3.pdf
Code:
https://github.com/luanfujun/deep-painterly-harmonization
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
The Netflix Data War
https://simplystatistics.org/2018/12/19/the-netflix-data-war/
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π£ @AI_Python_arXiv
β΄οΈ @AI_Python
https://simplystatistics.org/2018/12/19/the-netflix-data-war/
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π£ @AI_Python_arXiv
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The Relationship Between #MachineLearning and #AI
- Machine Learning exists without AI
- AI exists without Machine Learning
- New AI embeds Machine Learning
- Machine Learning rarely uses AI You
got all that? π€
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π£ @AI_Python_arXiv
β΄οΈ @AI_Python
- Machine Learning exists without AI
- AI exists without Machine Learning
- New AI embeds Machine Learning
- Machine Learning rarely uses AI You
got all that? π€
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
Why are freshers not getting a job? π€·ββοΈπ€·ββοΈ
I have tried to list down the top 3 reasons, as per my understanding. Would love to know as to how you would rank each one of them, in order of seriousness.
Example: If you find B to be the biggest reason, followed by A and C, your answer should be "BAC".
Also, if you find a reason deserving a place in the top 3, do mention the same.
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
I have tried to list down the top 3 reasons, as per my understanding. Would love to know as to how you would rank each one of them, in order of seriousness.
Example: If you find B to be the biggest reason, followed by A and C, your answer should be "BAC".
Also, if you find a reason deserving a place in the top 3, do mention the same.
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
Which #MachineLearning #Algorithm To Choose For My Problem ? π Linear Regression? Decision Tree? Random Forest? Boosting? SVM? #NeuralNetworks? K-Means? or OC-SVM?
πhttps://buff.ly/2qNEge1
#AI #DeepLearning #BigData #DataScience
βοΈ @AI_Python_EN
π£ @AI_Python_arXiv
β΄οΈ @AI_Python
πhttps://buff.ly/2qNEge1
#AI #DeepLearning #BigData #DataScience
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π£ @AI_Python_arXiv
β΄οΈ @AI_Python
10 Exciting Ideas of 2018 in NLP
A collection of 10 exciting and impactful ideas in 2018, by Sebastian Ruder: https://lnkd.in/ebb2Qix
#artificialinteligence #deeplearning #machinelearning #NLP #unsupervisedlearning
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A collection of 10 exciting and impactful ideas in 2018, by Sebastian Ruder: https://lnkd.in/ebb2Qix
#artificialinteligence #deeplearning #machinelearning #NLP #unsupervisedlearning
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π£ @AI_Python_arXiv
β΄οΈ @AI_Python