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5 Puzzles 21 Days. Can you solve it all?
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Sample Efficient Reinforcement Learning in Minecraft
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Measure sample efficiency and generalization in reinforcement learning using procedurally generated environments
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Self-driving RL on DeepRacer cars - From simulation to real world
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3D Seismic Image Interpretation by Machine Learning
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See Allfailed | 153028 | ||
graded | 109215 | ||
graded | 109213 |
5 Puzzles 21 Days. Can you solve it all?
Latest submissions
5 Puzzles 21 Days. Can you solve it all?
Latest submissions
See Allfailed | 152727 | ||
graded | 150974 | ||
graded | 150854 |
5 Puzzles 21 Days. Can you solve it all?
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A dataset and open-ended challenge for music recommendation research
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A benchmark for image-based food recognition
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See Allgraded | 109643 | ||
graded | 108956 | ||
graded | 108789 |
5 Puzzles, 3 Weeks. Can you solve them all? π
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Multi-agent RL in game environment. Train your Derklings, creatures with a neural network brain, to fight for you!
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Predicting smell of molecular compounds
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Classify images of snake species from around the world
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Find all the aircraft!
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5 Problems 21 Days. Can you solve it all?
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5 Puzzles, 3 Weeks | Can you solve them all?
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5 PROBLEMS 3 WEEKS. CAN YOU SOLVE THEM ALL?
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See Allfailed | 153028 | ||
graded | 109215 | ||
graded | 109213 |
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Grouping/Sorting players into their respective teams
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5 Problems 15 Days. Can you solve it all?
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5 PROBLEMS 3 WEEKS. CAN YOU SOLVE THEM ALL?
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See Allgraded | 82062 | ||
graded | 81854 | ||
graded | 81847 |
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Venomous Snake Classification
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Solve Sudoku puzzles!
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Detect water bodies from satellite Imagery
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See Allgraded | 82062 | ||
graded | 81854 | ||
graded | 81847 |
Predict Steering Angle
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Predicting wine quality
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DA Final Project challenges for Monsoon 2020
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Classifying Emotion from Texts
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Deshuffle the Shuffled Text
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Feature Engineering in Texts
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Predict Text from Sound
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Can you detect Icebergs in low visibility ?
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See Allgraded | 150974 | ||
graded | 150854 | ||
failed | 150645 |
Classify Facial Expressions
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Identify Words from silent video inputs.
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NLP Feature Engineering #2
Trouble getting submissions to run
Over 2 years agoI looked into the notebook you submitted in the submission #171169 and the error in our internal logs was IndexError: index 0 is out of bounds for axis 0 with size 0
occured on the line X1.append(df_saved_vocab[df_saved_vocab['word']==t]['min'].values[0])
. I tried executing the notebook locally with the private data and found out the error is due to the list returned by df_saved_vocab[df_saved_vocab['word']==t]['min'].values
had no elements ( []
) and when you tried to get the 0
index element by using .values[0]
it resulted in the above error IndexError: index 0 is out of bounds for axis 0 with size 0
occured` .
In Generate Predictions On Test Data phrase of evaluation, we have private test data of over 20k samples used for generating the predictions. In your df_saved_vocab.csv there are values of only 95 different words which can be insufficient given that our private test data has over 20k samples.
What I will suggest to try is -
- You can either generate the embeddings in the Prediction phase of the notebook
- You can generate the embeddings of top n most common English words and then save it in the
df_saved_vocab.csv
. - You can also add
try except
block in the.values[0]
to make sure that if this error occurs, you can append, for ex. ([0]
) to theX1
list.
I hope this explanation helps Let me know if you have any more doubts
Best
Shubhamai
Trouble getting submissions to run
Over 2 years agoHi mkeywood
I am looking into this issue and will get back to you asap
Best
Shubhamai
Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0:
Over 2 years agoHi pn1
The warning is due to because there are no GPUs in the evaluator. The evaluator in the NLP Feature Engineering puzzle only uses CPU for evaluation. This warning will not abort the evaluation. I hope this helps
Best,
Shubhamai
AI Blitz #6
How to deal with draws
Over 3 years agoStrange, the 9008.jpg of test doesnβt looks like a draw to me. Can you check if this is the right image.
Also, by illegal, do you only mean that in case of checkmate the player still have turn ? I am checking in my code to figure out the root of problem but can you share some samples of this case.
Shubhamai
How to deal with draws
Over 3 years agoHi boussif oussama .
I guess you are talking about Win prediction in which case can you please share more examples that have draws in the test set.
I am looking into the second issue and will give updates
Shubhamai
CHESS TRANSCRIPTION
About white passed pawn
Over 3 years agoNope, itβs not a mistake, we are not differentiating between black/white queen in the samples of this challenge, including test ground truth, so just put small q if you find moves which have conversion of pawn to queen. Enjoy
Food Recognition Challenge
More masks than bboxes?
Over 3 years agoHi, thanks for pointing this out! We are looking into this issue and giving updates asap
Detectron2 Colab Notebook from Data Exploration to Training the Model π
About 4 years agoHi Guys, Me Shubhamai, Machine Learning Engineer working extensively in the Deep Learning & Computer Vision field.
I have created a colab notebook for this competition which contains a lot of sections including data exploration/visualizations and making model & training it and things like that.
Here is the link to the colab notebook . I hope that it will help, i would also add more things into that soon.
IMGCOL
No one sample in new 'test_black_white_images-v2.zip'
Over 3 years ago(post withdrawn by author, will be automatically deleted in 24 hours unless flagged)
Seismic Facies Identification Challenge
[Explainer] Detectron2 & COCO Dataset π₯ β’ Web Application & Visualizations β’ End-to-End Baseline & Tensorflow
Almost 4 years agoSo, me Shubhamai and I have come up with these 3 things -
COCO Dataset & using Detectron2, MMDetection
YES! I have converted this dataset into COCO Dataset and which we train Mask-RCNN using Detectron2.
There we go boys - Colab Link
More things will be added so like this post RIGHT NOW
Web Application & Visualisation
https://seismic-facies-identification.herokuapp.com/
But this time, I found that a great preprocessing pipeline can help to model to find accurate features and increasing overall accuracy. But it kinda isnβt that easy as it looks β
So I made a Web Application based on that which allows you to play/experiment with many of the image preprocessing functions/methods, changing parameters or writing custom image preprocessing functions to experiment.
And it also contains all the visualizations from the colab notebook .
I hope that it will help you in making the perfect preprocessing pipelines .
End-to-End Baseline & Tensorflow
https://colab.research.google.com/drive/1t1hF_Vs4xIyLGMw_B9l1G6qzLBxLB5eG?usp=sharing
I have made a complete colab notebook from Data Exploration to Submitting Predictions. Here are some of the glimpse of the image visualization section!
And this 3D Plot!
Tables of Content -
- Setting our Workspace
- Data Exploration
- Image Preprocessing Techniqes
- Creating our Dataset
- Creating our Model
- Training the Model
- Evaluating the model
- Testing on test Data
- Generate More Data + Some tips & tricks
The main libraries covered in this notebook is β
- Tensorflow 2.0 & Keras
- Plotly
- cv2
and much moreβ¦
The model that i am using is UNet, pretty much standard in image segmentation. More is in the colab notebook!
I hope the colab notebook will help you get started in this competition or learning something new . If the notebook did help you, make sure to like the post. lol.
https://colab.research.google.com/drive/1t1hF_Vs4xIyLGMw_B9l1G6qzLBxLB5eG?usp=sharing
Please like the topic if this helps in any way possible . I really appreciate that
π Explained by the Community | Win 4 x DJI Mavic Drones
About 4 years agoHello Everyone!
Me Shubhamai, Machine Learning Engineer, and I am excitedly working on this competition because especially it a kind of 3D problem rather than 2D. Previously I made the complete google colab notebook from data exploration to submission. You can find the notebook here.
But this time, I found that a great preprocessing pipeline can help to model to find accurate features and increasing overall accuracy. But it kinda isnβt that easy as it looks β
So I made a Web Application based on that which allows you to play/experiment with many of the image preprocessing functions/methods, changing parameters or writing custom image preprocessing functions to experiment.
And it also contains all the visualizations from the colab notebook.
I hope that it will help you in making the perfect preprocessing pipelines and make sure you like the post . Thanks
π Explained by the Community | Win 4 x DJI Mavic Drones
About 4 years agoSure! Thanks for the suggestion . I will make changes to the color map soon!
π Explained by the Community | Win 4 x DJI Mavic Drones
About 4 years agoHi Everyone
I have made a complete colab notebook from Data Exploration to Submitting Predictions. Here are some of the glimpse of the image visualization section!
And this 3D Plot!
Tables of Content -
Setting our Workspace
Data Exploration
Image Preprocessing Techniqes
Creating our Dataset
Creating our Model
Training the Model
Evaluating the model
Testing on test Data
Generate More Data + Some tips & tricks
The main libraries covered in this notebook is β
- Tensorflow 2.0 & Keras
- Plotly
- cv2
and much moreβ¦
The model that i am using is UNet, pretty much standard in image segmentation. More is in the colab notebook!
I hope the colab notebook will help you get started in this competition or learning something new . If the notebook did help you, make sure to like the post. lol.
https://colab.research.google.com/drive/1t1hF_Vs4xIyLGMw_B9l1G6qzLBxLB5eG?usp=sharing
More things will be added soon!
By
AI for Good - AI Blitz #3
Explained by the Community | 100 CHF Prize contest π
About 4 years agoHi,
Me Shubhamai, i did the LNDST competition and here is the github repo https://github.com/Shubhamai/water-segmentation
Notebooks
-
π Food Recognition Challenge : Data Exploration & Baseline Food Recognition Challenge NotebookShubhamaiΒ· Almost 3 years ago
-
[Explainer] Detectron2 & COCO Dataset π₯ β’ Web Application & Visualizations β’ End-to-End Baseline & Tensorflow Detectron2 & COCO Dataset π₯ β’ Web Application & Visualizations β’ End-to-End Baseline & TensorflowShubhamaiΒ· Almost 4 years ago
Notebooks
-
[Getting Started Notebook] Obstacle Prediction A Getting Started notebook for Obstacle Prediction Puzzle of BlitzXI.ShubhamaicrowdΒ· About 3 years ago
Trouble getting submissions to run
Over 2 years agoUnfortunately, The logs for the Generate Predictions On Test Data part of the evaluation remain private and only available for admins. It is due to the private test data used in Generate Predictions On Test Data part of the evaluation.