{ "id": 323794, "title": "Notebooks To Help You Get Started!", "url": "/competitions/herbarium-2022-fgvc9/discussion/323794", "author_name": "", "post_date": "2022-05-08T11:59:14.124000", "votes": 15, "comment_count": 7, "views": 0, "content": "

'

\n

All right, listen up!
\nIn order to be successful in this Kaggle Competition: Herbarium-2022-fgvc9, you're going to need to start with the right tools.
\nThat's why I've got a list of notebooks for you to use as starters.

\n

Enjoy! <3

\n
\n

Herbarium Jax Flax Training Kfolds W B by @heyytanay

\n
\n

@heyytanay uses the k-fold cross-validation method and the Flax Jax for building the models.

\n
\n

If you're looking to learn more about the inner workings of KFolds or Flax Jax and get some serious training under your belt, look no further than this notebook! Using real-world examples and clear code snippets, you'll be able to walk away with a deep understanding of how KFolds works. Not to mention, the included logging function will make it easy to track your progress and evaluate your results.

\n
\n

Json Pandas Herbarium 2022 by @odins0n

\n
\n

The methods used by @odins0n are loading data into pandas, exploring it, and performing data transformations.

\n
\n

If you are looking to extract insights from a dataset and want to use pandas for data analysis, then the @odins0n notebook is for you. This notebook will show you how to load data into pandas, explore it, and perform data transformations. The dataset used in this notebook is the herbarium-2022-fgvc9 dataset. This dataset contains images of plants along with their annotations such as the name of the plant and its genus. You will learn how to use pandas to explore this dataset and extract insights from it.

\n
\n

Herbarium Flipping Through The Pages Of Memories by @ohseokkim

\n
\n

@ohseokkim uses a variety of methods, including many from image recognition.

\n
\n

I invite you to explore @ohseokkim notebook. As you flip through its pages, you'll encounter all sorts of colorful, vivid images and visualizations. I guarantee that you won't be able to put it down!

\n
\n

Herbarium 2022 Fast Exploratory Data Analysis by @vad13irt

\n
\n

@vad13irt uses methods such as visualization and easy-to-read text to explore data.

\n
\n

If you are looking to explore data in a fun and fast way, then the @vad13irt notebook is perfect for you. With its colorful charts and easy-to-read text, you will be able to explore your data in no time.

\n
\n

Kaggle Herbarium 2022 Long Tailed Learning by @mpwolke

\n
\n

@mpwolke shows us some important information about the long tailed distribution of the data!

\n
\n

This notebook contains exploratory data analysis of the Herbarium-2021 dataset. The analysis is thought-provoking, and the results are visually stunning. the author has provided a clear and concise explanation of each step of the analysis, making it easy for anyone to follow. This notebook is a valuable resource for anyone who wants to learn more about deep learning and data science.

\n
\n

Herbarium EDA Baseline Flash Efficientnet by @jirkaborovec

\n
\n

@jirkaborovec used Efficientnet to create a great baseline for the competition.

\n
\n

In order to achieve state-of-the-art performance for image classification, this notebook uses the best practices and latest techniques. By using a powerful deep learning library like torch, and a well-optimized neural network model, you can train your own classifier to identify objects in images with amazing accuracy.

\n
\n

Herbarium Lightning Flash Inference by @jirkaborovec

\n
\n

@jirkaborovec uses PyTorch Lighting for fast inference.

\n
\n

Want to be a top competitor on Kaggle? Check out @jirkaborovec's notebook which uses PyTorch Lighting. You'll find tips on how to set up your environment, as well as how to train and evaluate your model.

\n
\n

Fgvc 9 Starter EDA Tensorflow by @venkatkumar001

\n
\n

This article uses the TensorFlow library and provides example code to help readers get started.

\n
\n

If you are looking for a notebook that can help you get started with TensorFlow, then @venkatkumar001's notebook is a great resource. @venkatkumar001 provides a detailed explanation of how to get started with the library, and includes example code that you can use to get your own projects up and running. This notebook is an excellent starting point for anyone who wants to learn more about TensorFlow.

\n
\n

Exploration Preprocessing Baseline Cnn by @salaheddinelahmadi

\n
\n

This notebook uses techniques to explore, preprocess, and classify images with CNN.

\n
\n

@salaheddinelahmadi's notebook shows how to apply state-of-the-art deep learning techniques for exploring, preprocessing and classifying images. The examples are easy to follow and the results are impressive. If you're looking to get started in deep learning or image processing, this notebook is a great place to start.

\n
\n

Herbarium 2022 Pytorch Tresnet Train by @medali1992

\n
\n

@medali1992's work is great if you want to improve your skills in Pytorch, as well as to implement a world-class deep learning model.

\n
\n

If you are looking to improve your skills in Pytorch and machine learning, or if you simply want to see how a world-class deep learning model is implemented, then this notebook is for you. @medali1992, @medali1992, walks you through every step of the process from pre-processing the data to training the model and evaluating it on a validation set. You will see how powerful Pytorch can be, and by the end of this notebook you will be able to build your own state-of-the-art deep learning models.

\n
\n

Welcome Herbarium 2022 by @hamzaghanmi

\n
\n

@hamzaghanmi used tensorflow to create a welcome notebook for the competition.

\n
\n

This notebook is a must-read for any data scientist who wants to get started with TensorFlow. @hamzaghanmi has done an amazing job at walking through the various concepts and providing clear examples. The best part is that all of the code is provided, so you can follow along and gain practical experience. I highly recommend this notebook for anyone who wants to learn more about TensorFlow.

\n
\n

Herbarium 2022 Starter Sample Code by @brendanrappazzo

\n
\n

The methods used by @brendanrappazzo include clear and concise codes.

\n
\n

@brendanrappazzo is a wonderful notebook that will help you in your data science journey. The codes are clear and concise, and @brendanrappazzo's clean code flair makes the experience even more enjoyable.

\n
\n

North America Flora Herbarium Taxonomy by @mpwolke

\n
\n

@mpwolke uses the methods of data science to explore and present data on the flora of North America.

\n
\n

This Taxonomy Kaggle Notebook will take you on a journey as you explore the North America Flora. You'll get to see the different families of plants and their corresponding count data. The beauty of this notebook is that it's interactive; you can explore the data in a variety of ways.

\n
\n

Full Tutorial On Image Processing In Skimage by @bextuychiev

\n
\n

The methods used by @bextuychiev include walking through every step of image processing in Skimage, from loading an image to detecting edges and corners.

\n
\n

If you're looking to get into computer vision, or just want to improve your skills, then you need to go through this notebook. @bextuychiev walks you through every step of image processing in Skimage, from loading an image to detecting edges and corners. The code is clear and easy-to-follow, so you can quickly improve your skillset.

\n
\n

Herbarium 2022 Complete Starter Nb by @roshanr11

\n
\n

@roshanr11 uses a mix of basic and more advanced methods, to teach the reader about the world of machine learning.

\n
\n

If you are looking for an insightful and captivating introduction to the world of machine learning, look no further than @roshanr11's starter notebook. His thoughtful explanations and well-ordered tutorials will guide you smoothly from basic concepts to more advanced techniques. With @roshanr11's guidance, you'll be on your way to mastering this essential skill in no time!

", "messages": [ { "id": 1781312, "postDate": "2022-05-08T11:59:14.123Z", "content": "

'

\n

All right, listen up!
\nIn order to be successful in this Kaggle Competition: Herbarium-2022-fgvc9, you're going to need to start with the right tools.
\nThat's why I've got a list of notebooks for you to use as starters.

\n

Enjoy! <3

\n
\n

Herbarium Jax Flax Training Kfolds W B by @heyytanay

\n
\n

@heyytanay uses the k-fold cross-validation method and the Flax Jax for building the models.

\n
\n

If you're looking to learn more about the inner workings of KFolds or Flax Jax and get some serious training under your belt, look no further than this notebook! Using real-world examples and clear code snippets, you'll be able to walk away with a deep understanding of how KFolds works. Not to mention, the included logging function will make it easy to track your progress and evaluate your results.

\n
\n

Json Pandas Herbarium 2022 by @odins0n

\n
\n

The methods used by @odins0n are loading data into pandas, exploring it, and performing data transformations.

\n
\n

If you are looking to extract insights from a dataset and want to use pandas for data analysis, then the @odins0n notebook is for you. This notebook will show you how to load data into pandas, explore it, and perform data transformations. The dataset used in this notebook is the herbarium-2022-fgvc9 dataset. This dataset contains images of plants along with their annotations such as the name of the plant and its genus. You will learn how to use pandas to explore this dataset and extract insights from it.

\n
\n

Herbarium Flipping Through The Pages Of Memories by @ohseokkim

\n
\n

@ohseokkim uses a variety of methods, including many from image recognition.

\n
\n

I invite you to explore @ohseokkim notebook. As you flip through its pages, you'll encounter all sorts of colorful, vivid images and visualizations. I guarantee that you won't be able to put it down!

\n
\n

Herbarium 2022 Fast Exploratory Data Analysis by @vad13irt

\n
\n

@vad13irt uses methods such as visualization and easy-to-read text to explore data.

\n
\n

If you are looking to explore data in a fun and fast way, then the @vad13irt notebook is perfect for you. With its colorful charts and easy-to-read text, you will be able to explore your data in no time.

\n
\n

Kaggle Herbarium 2022 Long Tailed Learning by @mpwolke

\n
\n

@mpwolke shows us some important information about the long tailed distribution of the data!

\n
\n

This notebook contains exploratory data analysis of the Herbarium-2021 dataset. The analysis is thought-provoking, and the results are visually stunning. the author has provided a clear and concise explanation of each step of the analysis, making it easy for anyone to follow. This notebook is a valuable resource for anyone who wants to learn more about deep learning and data science.

\n
\n

Herbarium EDA Baseline Flash Efficientnet by @jirkaborovec

\n
\n

@jirkaborovec used Efficientnet to create a great baseline for the competition.

\n
\n

In order to achieve state-of-the-art performance for image classification, this notebook uses the best practices and latest techniques. By using a powerful deep learning library like torch, and a well-optimized neural network model, you can train your own classifier to identify objects in images with amazing accuracy.

\n
\n

Herbarium Lightning Flash Inference by @jirkaborovec

\n
\n

@jirkaborovec uses PyTorch Lighting for fast inference.

\n
\n

Want to be a top competitor on Kaggle? Check out @jirkaborovec's notebook which uses PyTorch Lighting. You'll find tips on how to set up your environment, as well as how to train and evaluate your model.

\n
\n

Fgvc 9 Starter EDA Tensorflow by @venkatkumar001

\n
\n

This article uses the TensorFlow library and provides example code to help readers get started.

\n
\n

If you are looking for a notebook that can help you get started with TensorFlow, then @venkatkumar001's notebook is a great resource. @venkatkumar001 provides a detailed explanation of how to get started with the library, and includes example code that you can use to get your own projects up and running. This notebook is an excellent starting point for anyone who wants to learn more about TensorFlow.

\n
\n

Exploration Preprocessing Baseline Cnn by @salaheddinelahmadi

\n
\n

This notebook uses techniques to explore, preprocess, and classify images with CNN.

\n
\n

@salaheddinelahmadi's notebook shows how to apply state-of-the-art deep learning techniques for exploring, preprocessing and classifying images. The examples are easy to follow and the results are impressive. If you're looking to get started in deep learning or image processing, this notebook is a great place to start.

\n
\n

Herbarium 2022 Pytorch Tresnet Train by @medali1992

\n
\n

@medali1992's work is great if you want to improve your skills in Pytorch, as well as to implement a world-class deep learning model.

\n
\n

If you are looking to improve your skills in Pytorch and machine learning, or if you simply want to see how a world-class deep learning model is implemented, then this notebook is for you. @medali1992, @medali1992, walks you through every step of the process from pre-processing the data to training the model and evaluating it on a validation set. You will see how powerful Pytorch can be, and by the end of this notebook you will be able to build your own state-of-the-art deep learning models.

\n
\n

Welcome Herbarium 2022 by @hamzaghanmi

\n
\n

@hamzaghanmi used tensorflow to create a welcome notebook for the competition.

\n
\n

This notebook is a must-read for any data scientist who wants to get started with TensorFlow. @hamzaghanmi has done an amazing job at walking through the various concepts and providing clear examples. The best part is that all of the code is provided, so you can follow along and gain practical experience. I highly recommend this notebook for anyone who wants to learn more about TensorFlow.

\n
\n

Herbarium 2022 Starter Sample Code by @brendanrappazzo

\n
\n

The methods used by @brendanrappazzo include clear and concise codes.

\n
\n

@brendanrappazzo is a wonderful notebook that will help you in your data science journey. The codes are clear and concise, and @brendanrappazzo's clean code flair makes the experience even more enjoyable.

\n
\n

North America Flora Herbarium Taxonomy by @mpwolke

\n
\n

@mpwolke uses the methods of data science to explore and present data on the flora of North America.

\n
\n

This Taxonomy Kaggle Notebook will take you on a journey as you explore the North America Flora. You'll get to see the different families of plants and their corresponding count data. The beauty of this notebook is that it's interactive; you can explore the data in a variety of ways.

\n
\n

Full Tutorial On Image Processing In Skimage by @bextuychiev

\n
\n

The methods used by @bextuychiev include walking through every step of image processing in Skimage, from loading an image to detecting edges and corners.

\n
\n

If you're looking to get into computer vision, or just want to improve your skills, then you need to go through this notebook. @bextuychiev walks you through every step of image processing in Skimage, from loading an image to detecting edges and corners. The code is clear and easy-to-follow, so you can quickly improve your skillset.

\n
\n

Herbarium 2022 Complete Starter Nb by @roshanr11

\n
\n

@roshanr11 uses a mix of basic and more advanced methods, to teach the reader about the world of machine learning.

\n
\n

If you are looking for an insightful and captivating introduction to the world of machine learning, look no further than @roshanr11's starter notebook. His thoughtful explanations and well-ordered tutorials will guide you smoothly from basic concepts to more advanced techniques. With @roshanr11's guidance, you'll be on your way to mastering this essential skill in no time!

", "rawMarkdown": "'\n\nAll right, listen up!\nIn order to be successful in this Kaggle Competition: Herbarium-2022-fgvc9, you're going to need to start with the right tools.\nThat's why I've got a list of notebooks for you to use as starters.\n\nEnjoy! <3\n\n_____\n\n\n**[Herbarium Jax Flax Training Kfolds W B](https://kaggle.com/heyytanay/herbarium-jax-flax-training-kfolds-w-b) by @heyytanay**\n>@heyytanay uses the k-fold cross-validation method and the Flax Jax for building the models.\n\nIf you're looking to learn more about the inner workings of KFolds or Flax Jax and get some serious training under your belt, look no further than this notebook! Using real-world examples and clear code snippets, you'll be able to walk away with a deep understanding of how KFolds works. Not to mention, the included logging function will make it easy to track your progress and evaluate your results.\n\n\n\n_____\n\n\n**[Json Pandas Herbarium 2022](https://kaggle.com/odins0n/json-pandas-herbarium-2022) by @odins0n**\n>The methods used by @odins0n are loading data into pandas, exploring it, and performing data transformations.\n\nIf you are looking to extract insights from a dataset and want to use pandas for data analysis, then the @odins0n notebook is for you. This notebook will show you how to load data into pandas, explore it, and perform data transformations. The dataset used in this notebook is the herbarium-2022-fgvc9 dataset. This dataset contains images of plants along with their annotations such as the name of the plant and its genus. You will learn how to use pandas to explore this dataset and extract insights from it.\n\n\n\n_____\n\n\n**[Herbarium Flipping Through The Pages Of Memories](https://kaggle.com/ohseokkim/herbarium-flipping-through-the-pages-of-memories) by @ohseokkim**\n>@ohseokkim uses a variety of methods, including many from image recognition.\n\nI invite you to explore @ohseokkim notebook. As you flip through its pages, you'll encounter all sorts of colorful, vivid images and visualizations. I guarantee that you won't be able to put it down!\n\n\n\n_____\n\n\n**[Herbarium 2022 Fast Exploratory Data Analysis](https://kaggle.com/vad13irt/herbarium-2022-fast-exploratory-data-analysis) by @vad13irt**\n>@vad13irt uses methods such as visualization and easy-to-read text to explore data.\n\nIf you are looking to explore data in a fun and fast way, then the @vad13irt notebook is perfect for you. With its colorful charts and easy-to-read text, you will be able to explore your data in no time.\n\n\n\n_____\n\n\n**[Kaggle Herbarium 2022 Long Tailed Learning](https://kaggle.com/mpwolke/kaggle-herbarium-2022-long-tailed-learning) by @mpwolke**\n>@mpwolke shows us some important information about the long tailed distribution of the data!\n\nThis notebook contains exploratory data analysis of the Herbarium-2021 dataset. The analysis is thought-provoking, and the results are visually stunning. the author has provided a clear and concise explanation of each step of the analysis, making it easy for anyone to follow. This notebook is a valuable resource for anyone who wants to learn more about deep learning and data science.\n\n\n\n_____\n\n\n\n**[Herbarium EDA Baseline Flash Efficientnet](https://kaggle.com/jirkaborovec/herbarium-eda-baseline-flash-efficientnet) by @jirkaborovec**\n>@jirkaborovec used Efficientnet to create a great baseline for the competition.\n\nIn order to achieve state-of-the-art performance for image classification, this notebook uses the best practices and latest techniques. By using a powerful deep learning library like torch, and a well-optimized neural network model, you can train your own classifier to identify objects in images with amazing accuracy.\n\n\n\n_____\n\n\n**[Herbarium Lightning Flash Inference](https://kaggle.com/jirkaborovec/herbarium-lightning-flash-inference) by @jirkaborovec**\n>@jirkaborovec uses PyTorch Lighting for fast inference.\n\nWant to be a top competitor on Kaggle? Check out @jirkaborovec's notebook which uses PyTorch Lighting. You'll find tips on how to set up your environment, as well as how to train and evaluate your model.\n\n\n\n_____\n\n\n**[Fgvc 9 Starter EDA Tensorflow](https://kaggle.com/venkatkumar001/fgvc-9-starter-eda-tensorflow) by @venkatkumar001**\n>This article uses the TensorFlow library and provides example code to help readers get started.\n\nIf you are looking for a notebook that can help you get started with TensorFlow, then @venkatkumar001's notebook is a great resource. @venkatkumar001 provides a detailed explanation of how to get started with the library, and includes example code that you can use to get your own projects up and running. This notebook is an excellent starting point for anyone who wants to learn more about TensorFlow.\n\n\n\n_____\n\n\n**[Exploration Preprocessing Baseline Cnn](https://kaggle.com/salaheddinelahmadi/exploration-preprocessing-baseline-cnn) by @salaheddinelahmadi**\n>This notebook uses techniques to explore, preprocess, and classify images with CNN.\n\n@salaheddinelahmadi's notebook shows how to apply state-of-the-art deep learning techniques for exploring, preprocessing and classifying images. The examples are easy to follow and the results are impressive. If you're looking to get started in deep learning or image processing, this notebook is a great place to start.\n\n\n\n_____\n\n\n**[Herbarium 2022 Pytorch Tresnet Train](https://kaggle.com/medali1992/herbarium-2022-pytorch-tresnet-train) by @medali1992**\n>@medali1992's work is great if you want to improve your skills in Pytorch, as well as to implement a world-class deep learning model.\n\nIf you are looking to improve your skills in Pytorch and machine learning, or if you simply want to see how a world-class deep learning model is implemented, then this notebook is for you. @medali1992, @medali1992, walks you through every step of the process from pre-processing the data to training the model and evaluating it on a validation set. You will see how powerful Pytorch can be, and by the end of this notebook you will be able to build your own state-of-the-art deep learning models.\n\n\n\n_____\n\n\n**[Welcome Herbarium 2022](https://kaggle.com/hamzaghanmi/welcome-herbarium-2022) by @hamzaghanmi**\n>@hamzaghanmi used tensorflow to create a welcome notebook for the competition.\n\nThis notebook is a must-read for any data scientist who wants to get started with TensorFlow. @hamzaghanmi has done an amazing job at walking through the various concepts and providing clear examples. The best part is that all of the code is provided, so you can follow along and gain practical experience. I highly recommend this notebook for anyone who wants to learn more about TensorFlow.\n\n\n\n_____\n\n\n**[Herbarium 2022 Starter Sample Code](https://kaggle.com/brendanrappazzo/herbarium-2022-starter-sample-code) by @brendanrappazzo**\n>The methods used by @brendanrappazzo include clear and concise codes.\n\n@brendanrappazzo is a wonderful notebook that will help you in your data science journey. The codes are clear and concise, and @brendanrappazzo's clean code flair makes the experience even more enjoyable.\n\n\n\n_____\n\n\n**[North America Flora Herbarium Taxonomy](https://kaggle.com/mpwolke/north-america-flora-herbarium-taxonomy) by @mpwolke**\n>@mpwolke uses the methods of data science to explore and present data on the flora of North America.\n\nThis Taxonomy Kaggle Notebook will take you on a journey as you explore the North America Flora. You'll get to see the different families of plants and their corresponding count data. The beauty of this notebook is that it's interactive; you can explore the data in a variety of ways.\n\n\n\n_____\n\n\n**[Full Tutorial On Image Processing In Skimage](https://kaggle.com/bextuychiev/full-tutorial-on-image-processing-in-skimage) by @bextuychiev**\n>The methods used by @bextuychiev include walking through every step of image processing in Skimage, from loading an image to detecting edges and corners.\n\nIf you're looking to get into computer vision, or just want to improve your skills, then you need to go through this notebook. @bextuychiev walks you through every step of image processing in Skimage, from loading an image to detecting edges and corners. The code is clear and easy-to-follow, so you can quickly improve your skillset.\n\n\n_____\n\n\n**[Herbarium 2022 Complete Starter Nb](https://kaggle.com/roshanr11/herbarium-2022-complete-starter-nb) by @roshanr11**\n>@roshanr11 uses a mix of basic and more advanced methods, to teach the reader about the world of machine learning.\n\nIf you are looking for an insightful and captivating introduction to the world of machine learning, look no further than @roshanr11's starter notebook. His thoughtful explanations and well-ordered tutorials will guide you smoothly from basic concepts to more advanced techniques. With @roshanr11's guidance, you'll be on your way to mastering this essential skill in no time!\n\n\n", "votes": 15 }, { "id": 1781486, "postDate": "2022-05-08T15:02:03.417Z", "content": "

Very good post! Keep up the great work!

", "rawMarkdown": "Very good post! Keep up the great work!", "votes": 1 }, { "id": 1781356, "postDate": "2022-05-08T12:39:47.897Z", "content": "

Thank you @satoshidatamoto. You just compiled everything needed.

", "rawMarkdown": "Thank you @satoshidatamoto. You just compiled everything needed.", "votes": 1 }, { "id": 1781318, "postDate": "2022-05-08T12:07:45.783Z", "content": "

Thanks for sharing, Buddy! you r clearly follow-through process of the competition @satoshidatamoto ๐Ÿ‘Œ
\nstarter clear approach (good explanation of notebook details), I like it, a way of representing all things๐Ÿ˜

", "rawMarkdown": "Thanks for sharing, Buddy! you r clearly follow-through process of the competition @satoshidatamoto ๐Ÿ‘Œ\nstarter clear approach (good explanation of notebook details), I like it, a way of representing all things๐Ÿ˜", "votes": 1 }, { "id": 1781938, "postDate": "2022-05-09T05:17:33.930Z", "content": "

Thank you so much @satoshidatamoto . This is going to help us a lot ๐Ÿ™Œ

", "rawMarkdown": "Thank you so much @satoshidatamoto . This is going to help us a lot ๐Ÿ™Œ" }, { "id": 1781605, "postDate": "2022-05-08T17:50:32.710Z", "content": "

Thank you for mentioning my notebook.
\nI will share an inference notebook and a notebook on how to use arcface for this competion.
\nBig thanks to @yasufuminakama for his baseline notebooks.

", "rawMarkdown": "Thank you for mentioning my notebook.\nI will share an inference notebook and a notebook on how to use arcface for this competion.\nBig thanks to @yasufuminakama for his baseline notebooks." }, { "id": 1786090, "postDate": "2022-05-12T15:45:06.180Z", "content": "

Thanks, @satoshidatamoto

", "rawMarkdown": "Thanks, @satoshidatamoto " }, { "id": 1782479, "postDate": "2022-05-09T16:01:05.420Z", "content": "

Thank you so much for the mention :)

", "rawMarkdown": "Thank you so much for the mention :)" } ], "comments": [ { "id": 1781486, "author_name": "Ravi Ramakrishnan", "author_url": "", "post_date": "2022-05-08T15:02:03.417000", "content": "

Very good post! Keep up the great work!

", "votes": 1, "replies": [] }, { "id": 1781356, "author_name": "Muhammed Tausif", "author_url": "", "post_date": "2022-05-08T12:39:47.897000", "content": "

Thank you @satoshidatamoto. You just compiled everything needed.

", "votes": 1, "replies": [] }, { "id": 1781318, "author_name": "VK", "author_url": "", "post_date": "2022-05-08T12:07:45.783000", "content": "

Thanks for sharing, Buddy! you r clearly follow-through process of the competition @satoshidatamoto ๐Ÿ‘Œ
\nstarter clear approach (good explanation of notebook details), I like it, a way of representing all things๐Ÿ˜

", "votes": 1, "replies": [] }, { "id": 1781938, "author_name": "Ansh Sarkar", "author_url": "", "post_date": "2022-05-09T05:17:33.930000", "content": "

Thank you so much @satoshidatamoto . This is going to help us a lot ๐Ÿ™Œ

", "votes": 0, "replies": [] }, { "id": 1781605, "author_name": "Med Ali Bouchhioua", "author_url": "", "post_date": "2022-05-08T17:50:32.710000", "content": "

Thank you for mentioning my notebook.
\nI will share an inference notebook and a notebook on how to use arcface for this competion.
\nBig thanks to @yasufuminakama for his baseline notebooks.

", "votes": 0, "replies": [] }, { "id": 1786090, "author_name": "Hamza", "author_url": "", "post_date": "2022-05-12T15:45:06.180000", "content": "

Thanks, @satoshidatamoto

", "votes": 0, "replies": [] }, { "id": 1782479, "author_name": "Tanay Mehta", "author_url": "", "post_date": "2022-05-09T16:01:05.420000", "content": "

Thank you so much for the mention :)

", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1781312": "'\n\nAll right, listen up!\nIn order to be successful in this Kaggle Competition: Herbarium-2022-fgvc9, you're going to need to start with the right tools.\nThat's why I've got a list of notebooks for you to use as starters.\n\nEnjoy! <3\n\n_____\n\n\n**[Herbarium Jax Flax Training Kfolds W B](https://kaggle.com/heyytanay/herbarium-jax-flax-training-kfolds-w-b) by @heyytanay**\n>@heyytanay uses the k-fold cross-validation method and the Flax Jax for building the models.\n\nIf you're looking to learn more about the inner workings of KFolds or Flax Jax and get some serious training under your belt, look no further than this notebook! Using real-world examples and clear code snippets, you'll be able to walk away with a deep understanding of how KFolds works. Not to mention, the included logging function will make it easy to track your progress and evaluate your results.\n\n\n\n_____\n\n\n**[Json Pandas Herbarium 2022](https://kaggle.com/odins0n/json-pandas-herbarium-2022) by @odins0n**\n>The methods used by @odins0n are loading data into pandas, exploring it, and performing data transformations.\n\nIf you are looking to extract insights from a dataset and want to use pandas for data analysis, then the @odins0n notebook is for you. This notebook will show you how to load data into pandas, explore it, and perform data transformations. The dataset used in this notebook is the herbarium-2022-fgvc9 dataset. This dataset contains images of plants along with their annotations such as the name of the plant and its genus. You will learn how to use pandas to explore this dataset and extract insights from it.\n\n\n\n_____\n\n\n**[Herbarium Flipping Through The Pages Of Memories](https://kaggle.com/ohseokkim/herbarium-flipping-through-the-pages-of-memories) by @ohseokkim**\n>@ohseokkim uses a variety of methods, including many from image recognition.\n\nI invite you to explore @ohseokkim notebook. As you flip through its pages, you'll encounter all sorts of colorful, vivid images and visualizations. I guarantee that you won't be able to put it down!\n\n\n\n_____\n\n\n**[Herbarium 2022 Fast Exploratory Data Analysis](https://kaggle.com/vad13irt/herbarium-2022-fast-exploratory-data-analysis) by @vad13irt**\n>@vad13irt uses methods such as visualization and easy-to-read text to explore data.\n\nIf you are looking to explore data in a fun and fast way, then the @vad13irt notebook is perfect for you. With its colorful charts and easy-to-read text, you will be able to explore your data in no time.\n\n\n\n_____\n\n\n**[Kaggle Herbarium 2022 Long Tailed Learning](https://kaggle.com/mpwolke/kaggle-herbarium-2022-long-tailed-learning) by @mpwolke**\n>@mpwolke shows us some important information about the long tailed distribution of the data!\n\nThis notebook contains exploratory data analysis of the Herbarium-2021 dataset. The analysis is thought-provoking, and the results are visually stunning. the author has provided a clear and concise explanation of each step of the analysis, making it easy for anyone to follow. This notebook is a valuable resource for anyone who wants to learn more about deep learning and data science.\n\n\n\n_____\n\n\n\n**[Herbarium EDA Baseline Flash Efficientnet](https://kaggle.com/jirkaborovec/herbarium-eda-baseline-flash-efficientnet) by @jirkaborovec**\n>@jirkaborovec used Efficientnet to create a great baseline for the competition.\n\nIn order to achieve state-of-the-art performance for image classification, this notebook uses the best practices and latest techniques. By using a powerful deep learning library like torch, and a well-optimized neural network model, you can train your own classifier to identify objects in images with amazing accuracy.\n\n\n\n_____\n\n\n**[Herbarium Lightning Flash Inference](https://kaggle.com/jirkaborovec/herbarium-lightning-flash-inference) by @jirkaborovec**\n>@jirkaborovec uses PyTorch Lighting for fast inference.\n\nWant to be a top competitor on Kaggle? Check out @jirkaborovec's notebook which uses PyTorch Lighting. You'll find tips on how to set up your environment, as well as how to train and evaluate your model.\n\n\n\n_____\n\n\n**[Fgvc 9 Starter EDA Tensorflow](https://kaggle.com/venkatkumar001/fgvc-9-starter-eda-tensorflow) by @venkatkumar001**\n>This article uses the TensorFlow library and provides example code to help readers get started.\n\nIf you are looking for a notebook that can help you get started with TensorFlow, then @venkatkumar001's notebook is a great resource. @venkatkumar001 provides a detailed explanation of how to get started with the library, and includes example code that you can use to get your own projects up and running. This notebook is an excellent starting point for anyone who wants to learn more about TensorFlow.\n\n\n\n_____\n\n\n**[Exploration Preprocessing Baseline Cnn](https://kaggle.com/salaheddinelahmadi/exploration-preprocessing-baseline-cnn) by @salaheddinelahmadi**\n>This notebook uses techniques to explore, preprocess, and classify images with CNN.\n\n@salaheddinelahmadi's notebook shows how to apply state-of-the-art deep learning techniques for exploring, preprocessing and classifying images. The examples are easy to follow and the results are impressive. If you're looking to get started in deep learning or image processing, this notebook is a great place to start.\n\n\n\n_____\n\n\n**[Herbarium 2022 Pytorch Tresnet Train](https://kaggle.com/medali1992/herbarium-2022-pytorch-tresnet-train) by @medali1992**\n>@medali1992's work is great if you want to improve your skills in Pytorch, as well as to implement a world-class deep learning model.\n\nIf you are looking to improve your skills in Pytorch and machine learning, or if you simply want to see how a world-class deep learning model is implemented, then this notebook is for you. @medali1992, @medali1992, walks you through every step of the process from pre-processing the data to training the model and evaluating it on a validation set. You will see how powerful Pytorch can be, and by the end of this notebook you will be able to build your own state-of-the-art deep learning models.\n\n\n\n_____\n\n\n**[Welcome Herbarium 2022](https://kaggle.com/hamzaghanmi/welcome-herbarium-2022) by @hamzaghanmi**\n>@hamzaghanmi used tensorflow to create a welcome notebook for the competition.\n\nThis notebook is a must-read for any data scientist who wants to get started with TensorFlow. @hamzaghanmi has done an amazing job at walking through the various concepts and providing clear examples. The best part is that all of the code is provided, so you can follow along and gain practical experience. I highly recommend this notebook for anyone who wants to learn more about TensorFlow.\n\n\n\n_____\n\n\n**[Herbarium 2022 Starter Sample Code](https://kaggle.com/brendanrappazzo/herbarium-2022-starter-sample-code) by @brendanrappazzo**\n>The methods used by @brendanrappazzo include clear and concise codes.\n\n@brendanrappazzo is a wonderful notebook that will help you in your data science journey. The codes are clear and concise, and @brendanrappazzo's clean code flair makes the experience even more enjoyable.\n\n\n\n_____\n\n\n**[North America Flora Herbarium Taxonomy](https://kaggle.com/mpwolke/north-america-flora-herbarium-taxonomy) by @mpwolke**\n>@mpwolke uses the methods of data science to explore and present data on the flora of North America.\n\nThis Taxonomy Kaggle Notebook will take you on a journey as you explore the North America Flora. You'll get to see the different families of plants and their corresponding count data. The beauty of this notebook is that it's interactive; you can explore the data in a variety of ways.\n\n\n\n_____\n\n\n**[Full Tutorial On Image Processing In Skimage](https://kaggle.com/bextuychiev/full-tutorial-on-image-processing-in-skimage) by @bextuychiev**\n>The methods used by @bextuychiev include walking through every step of image processing in Skimage, from loading an image to detecting edges and corners.\n\nIf you're looking to get into computer vision, or just want to improve your skills, then you need to go through this notebook. @bextuychiev walks you through every step of image processing in Skimage, from loading an image to detecting edges and corners. The code is clear and easy-to-follow, so you can quickly improve your skillset.\n\n\n_____\n\n\n**[Herbarium 2022 Complete Starter Nb](https://kaggle.com/roshanr11/herbarium-2022-complete-starter-nb) by @roshanr11**\n>@roshanr11 uses a mix of basic and more advanced methods, to teach the reader about the world of machine learning.\n\nIf you are looking for an insightful and captivating introduction to the world of machine learning, look no further than @roshanr11's starter notebook. His thoughtful explanations and well-ordered tutorials will guide you smoothly from basic concepts to more advanced techniques. With @roshanr11's guidance, you'll be on your way to mastering this essential skill in no time!\n\n\n", "1781486": "Very good post! Keep up the great work!", "1781356": "Thank you @satoshidatamoto. You just compiled everything needed.", "1781318": "Thanks for sharing, Buddy! you r clearly follow-through process of the competition @satoshidatamoto ๐Ÿ‘Œ\nstarter clear approach (good explanation of notebook details), I like it, a way of representing all things๐Ÿ˜", "1781938": "Thank you so much @satoshidatamoto . This is going to help us a lot ๐Ÿ™Œ", "1781605": "Thank you for mentioning my notebook.\nI will share an inference notebook and a notebook on how to use arcface for this competion.\nBig thanks to @yasufuminakama for his baseline notebooks.", "1786090": "Thanks, @satoshidatamoto ", "1782479": "Thank you so much for the mention :)" } }