I just got access to GitHub's Codespaces and it's amazing!

Abhishek Thakur · Beginner ·📐 ML Fundamentals ·5y ago

Key Takeaways

The video demonstrates GitHub's Codespaces, a cloud-based development environment that allows users to code in the browser, and showcases its features such as instant development environment, Visual Studio Code experience, and live sharing collaboration.

Full Transcript

hello everyone and welcome to my new video just just like an hour ago i got access to github code spaces and it's in beta and i got access to that and uh in this video i'm going to show you how it looks like so i'm totally blown away by this and this feature and i've always loved coding the browser because i i don't want to have a laptop with uh very high specifications so what is code spaces let's take a look at that so as you can see in the background this is the code spaces page that we have and um it's an instant development environment it says there so you can get the full visual studio code experience without leaving github and right now people who have applied for early access are getting it so i got it and the best way to look at it would be to just um try it right so here is one of the repositories that i have and to start code spaces in this repo what i do is i just click on code and click on open with code spaces so you can see that shows no active code spaces so what do we do we create we click on new code space so now it's opening a code space environment for me and this step is going to take maybe couple of minutes so let's wait so you can see like it has opened a visual studio code for me and everything is happening inside web browser it's so so awesome and uh now it has opened my repository and i can do whatever i want here so let's see let's see what features does it have uh let me increase the size a bit okay so i think this is quite good and now it looks like one of my videos right so i've always been coding in the browser so it now it's configuring my workspace so we can see some progress logs if we want basically it doesn't show me anything there and let me remove the theme so this is the original theme that you have that's the visual studio white theme and you can go to uh menu and change the theme there no sorry it's in the settings and change the color theme there so you have you have many different color themes to choose from i like the dark one so i'm just going to take the visual studio dark theme and now it's going to set up the theme for me so it seems like it's not setting up the theme for me because it's still configuring so i would i would wait for some time so that it finishes all the configurations and then we will set up the theme first theme is the most important thing right i think it has done its processing and setting up so we go to let me increase the size of this again for you so that you can see properly and we go to these settings and then color theme and choose dark and that's seems nice right so it's like my coding environment now and uh you you can click on any file like you have the requirements setup.buy you it's it's just the whole environment the python environment and you can see that creates this python and 3.8 right so just be careful of that you have to include it in git ignore otherwise when you commit it's going to add this to your git repository and you don't want to do that other than that let's see what else do we have we have extensions so some of the extensions are pre-installed and we can probably add python to it so it seems like python is there and it requires a reload so let's reload okay so that didn't take much time which is good and yeah it's some sometimes it's loading stuff but when when it has finished loading everything works really fast i've already tried it so now it has python so it should be it should give me some environment here so let's see the files that we have okay so now it tells me okay i can change the python interpreter so you have the python so it seems like the python extension is loading and uh yeah it tells you that you they have found a python environment also so which is nice um okay i will click on yes okay and this one i'm just closing so now it's also telling me that i can install pylint so let's install pilot um okay so now it has this python 3.8 environment python and 3.8 so so now we are in this environment and let's select the python interpreter 383 okay um okay maybe i didn't install it in this environment so let me install violent again okay so i have file int and now uh i can install the other things right so i'm not going to install a lot of uh libraries in this one i'm just going to show you like things are working here so you can go and play around with code spaces when you have access to it so i can just do clip install ticket name and it installed qdm for me and now uh i have it here and so let's see let's go to data loaders image classification and here i'm not using i'm not using tqdm in this one okay maybe i can search for it so search function also works fine so uh you see like i i have uh tqdm here so now i can probably click on uh control click on tqdm where i'm using it and so find also works perfectly fine and now it will show me the suggestions so because i have installed tkdm so let's see so i can click on tqdm and it should take me there so it's taking a little bit of time it's not taking me there let's see if i type something it doesn't suggest me anything no it's not suggesting me anything that's not very good yeah so like uh if i'm writing len so if i have a function so it's suggesting me but it was taking me to tqdm before i don't know why it's not working now but anyways it will work oh yeah now it works so you can install any kind of libraries you want so this will be your code spaces then you can turn it off and you if you have if you're using visual studio code locally you can also connect to this code space here and one more cool thing that i like is this live share feature so let's see if the live share works uh let me change the size a little bit okay so here you can see like now i can start collaboration so i can just click on this and it will start a live sharing session so it has started a live sharing session and then i can add the contributors to this repository uh or i can invite someone okay i can just have a uh session which is read only so i click on invite session and tells me that invite link has been copied to clipboard so let me open another browser and let's see what happens here so it will it you you can open it using vs code also um so when you open it in another browser that you cannot see right now it has opened another session for me so where where you can sign in or where you can uh join as a guest so now here it says that uh rb2 anonymous and read only that's me from another browser i have asked to join so i accept it and now i can see this new user here and the other user can also that other user can see what i'm doing so it's it's super cool for sharing code it's super easy uh like collaborating doing some kind of pair programming and you i can also remove the user and go back to my files one more cool thing is whatever changes you make you can always use the git commands so that's that's very nice so i can make all the changes i want in this environment i can modify this environment as much as i want and it's always going to be there so i know that you maybe you cannot train deep learning models in this environment and i don't know if you can connect an external machine to uh this environment so that it uses the resources from that machine i don't know if the feature is there yet but maybe hopefully soon in the future um so that's it for today's video i hope you like it and uh let me know how you find code spaces if you already have access to it um in the comments box and tell me uh about new videos that you want to see in future and see you bye

Original Description

NOTE: This is *not* a sponsored/promotional video. I just got access to #GitHub #Codespaces and it's amazing! Check it out in action in this video! Please subscribe and like the video to help me keep motivated to make awesome videos like this one. :) To buy my book, Approaching (Almost) Any Machine Learning problem, please visit: https://bit.ly/buyaaml Follow me on: Twitter: https://twitter.com/abhi1thakur LinkedIn: https://www.linkedin.com/in/abhi1thakur/ Kaggle: https://kaggle.com/abhishek
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Playlist

Uploads from Abhishek Thakur · Abhishek Thakur · 48 of 60

1 Episode 1.1: Intro and building a machine learning framework
Episode 1.1: Intro and building a machine learning framework
Abhishek Thakur
2 Episode 1.2: Building an inference for the machine learning framework
Episode 1.2: Building an inference for the machine learning framework
Abhishek Thakur
3 Episode 2: A Cross Validation Framework
Episode 2: A Cross Validation Framework
Abhishek Thakur
4 Tips N Tricks #2: Setting up development environment for machine learning
Tips N Tricks #2: Setting up development environment for machine learning
Abhishek Thakur
5 Episode 3: Handling Categorical Features in Machine Learning Problems
Episode 3: Handling Categorical Features in Machine Learning Problems
Abhishek Thakur
6 BERT on Steroids: Fine-tuning BERT for a dataset using PyTorch and Google Cloud TPUs
BERT on Steroids: Fine-tuning BERT for a dataset using PyTorch and Google Cloud TPUs
Abhishek Thakur
7 Special Announcement: Approaching (almost) any machine learning problem
Special Announcement: Approaching (almost) any machine learning problem
Abhishek Thakur
8 Training BERT Language Model From Scratch On TPUs
Training BERT Language Model From Scratch On TPUs
Abhishek Thakur
9 Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-1)
Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-1)
Abhishek Thakur
10 Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-2)
Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-2)
Abhishek Thakur
11 Episode 4: Simple and Basic Binary Classification Metrics
Episode 4: Simple and Basic Binary Classification Metrics
Abhishek Thakur
12 Training Sentiment Model Using BERT and Serving it with Flask API
Training Sentiment Model Using BERT and Serving it with Flask API
Abhishek Thakur
13 Episode 5: Entity Embeddings for Categorical Variables
Episode 5: Entity Embeddings for Categorical Variables
Abhishek Thakur
14 Tips N Tricks #5: 3 Simple and Easy Ways to Cache Functions in Python
Tips N Tricks #5: 3 Simple and Easy Ways to Cache Functions in Python
Abhishek Thakur
15 Multi-Lingual Toxic Comment Classification using BERT and TPUs with PyTorch
Multi-Lingual Toxic Comment Classification using BERT and TPUs with PyTorch
Abhishek Thakur
16 Text Extraction From a Corpus Using BERT (AKA Question Answering)
Text Extraction From a Corpus Using BERT (AKA Question Answering)
Abhishek Thakur
17 10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show
10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show
Abhishek Thakur
18 Data Processing For Question & Answering Systems: BERT vs. RoBERTa
Data Processing For Question & Answering Systems: BERT vs. RoBERTa
Abhishek Thakur
19 Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously
Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously
Abhishek Thakur
20 Sentencepiece Tokenizer With Offsets For T5, ALBERT, XLM-RoBERTa And Many More
Sentencepiece Tokenizer With Offsets For T5, ALBERT, XLM-RoBERTa And Many More
Abhishek Thakur
21 Talks # 1:Andrey Lukyanenko - Handwritten digit recognition w/ a twist &  topic modelling over time
Talks # 1:Andrey Lukyanenko - Handwritten digit recognition w/ a twist & topic modelling over time
Abhishek Thakur
22 Episode 6: Simple and Basic Evaluation Metrics For Regression
Episode 6: Simple and Basic Evaluation Metrics For Regression
Abhishek Thakur
23 Talks # 2: Subhaditya Mukherjee - Image restoration using Deep Learning: Dehazing
Talks # 2: Subhaditya Mukherjee - Image restoration using Deep Learning: Dehazing
Abhishek Thakur
24 Basic git commands everyone should know about
Basic git commands everyone should know about
Abhishek Thakur
25 How do I start my career in Data Science?
How do I start my career in Data Science?
Abhishek Thakur
26 Talks # 3: Lorenzo Ampil - Introduction to T5 for Sentiment Span Extraction
Talks # 3: Lorenzo Ampil - Introduction to T5 for Sentiment Span Extraction
Abhishek Thakur
27 Detecting Skin Cancer (Melanoma) With Deep Learning
Detecting Skin Cancer (Melanoma) With Deep Learning
Abhishek Thakur
28 Talks # 4: Sebastien Fischman - Pytorch-TabNet: Beating XGBoost on Tabular Data Using Deep Learning
Talks # 4: Sebastien Fischman - Pytorch-TabNet: Beating XGBoost on Tabular Data Using Deep Learning
Abhishek Thakur
29 Build a web-app to serve a deep learning model for skin cancer detection
Build a web-app to serve a deep learning model for skin cancer detection
Abhishek Thakur
30 Talks # 5: Parul Pandey: Data Science, Diversity and Kaggle
Talks # 5: Parul Pandey: Data Science, Diversity and Kaggle
Abhishek Thakur
31 Implementing original U-Net from scratch using PyTorch
Implementing original U-Net from scratch using PyTorch
Abhishek Thakur
32 Tips N Tricks # 8: Using automatic mixed precision training with PyTorch 1.6
Tips N Tricks # 8: Using automatic mixed precision training with PyTorch 1.6
Abhishek Thakur
33 Talks # 6: Mani Sarkar: From backend development to machine learning
Talks # 6: Mani Sarkar: From backend development to machine learning
Abhishek Thakur
34 Dockerizing the skin cancer detection web application
Dockerizing the skin cancer detection web application
Abhishek Thakur
35 How to train a deep learning model using docker?
How to train a deep learning model using docker?
Abhishek Thakur
36 Building an entity extraction model using BERT
Building an entity extraction model using BERT
Abhishek Thakur
37 Train custom object detection model with YOLO V5
Train custom object detection model with YOLO V5
Abhishek Thakur
38 Talks # 7: Moez Ali: Machine learning with PyCaret
Talks # 7: Moez Ali: Machine learning with PyCaret
Abhishek Thakur
39 How to convert almost any PyTorch model to ONNX and serve it using flask
How to convert almost any PyTorch model to ONNX and serve it using flask
Abhishek Thakur
40 Hyperparameter Optimization: This Tutorial Is All You Need
Hyperparameter Optimization: This Tutorial Is All You Need
Abhishek Thakur
41 I finally got a copy of "Approaching (Almost) Any Machine Learning Problem"
I finally got a copy of "Approaching (Almost) Any Machine Learning Problem"
Abhishek Thakur
42 Captcha recognition using PyTorch (Convolutional-RNN + CTC Loss)
Captcha recognition using PyTorch (Convolutional-RNN + CTC Loss)
Abhishek Thakur
43 Live Q&A: Getting Started With Data Science
Live Q&A: Getting Started With Data Science
Abhishek Thakur
44 WTFML: Simple, reusable code for PyTorch models
WTFML: Simple, reusable code for PyTorch models
Abhishek Thakur
45 Talks # 8: Sebastián Ramírez; Build a machine learning API  from scratch  with FastAPI
Talks # 8: Sebastián Ramírez; Build a machine learning API from scratch with FastAPI
Abhishek Thakur
46 Data Science PC Configs: From Low Range to Super-High Range
Data Science PC Configs: From Low Range to Super-High Range
Abhishek Thakur
47 BERT Model Architectures For Semantic Similarity
BERT Model Architectures For Semantic Similarity
Abhishek Thakur
I just got access to GitHub's Codespaces and it's amazing!
I just got access to GitHub's Codespaces and it's amazing!
Abhishek Thakur
49 Talks # 9: Vladimir Iglovikov; Detecting Masked Faces In The Pandemic World
Talks # 9: Vladimir Iglovikov; Detecting Masked Faces In The Pandemic World
Abhishek Thakur
50 Tips To Build A Good Data Science / Machine Learning Project (For Your Portfolio)
Tips To Build A Good Data Science / Machine Learning Project (For Your Portfolio)
Abhishek Thakur
51 Docker For Data Scientists
Docker For Data Scientists
Abhishek Thakur
52 How To Become A Data Scientist In 1 Year (Learn From A Real World Example)
How To Become A Data Scientist In 1 Year (Learn From A Real World Example)
Abhishek Thakur
53 Talks # 10: Tanishq Abraham; What are CycleGANs? (a novel deep learning tool in pathology)
Talks # 10: Tanishq Abraham; What are CycleGANs? (a novel deep learning tool in pathology)
Abhishek Thakur
54 Deploy Any Machine Learning Or Deep Learning Model On Google Cloud Platform (App Engine)
Deploy Any Machine Learning Or Deep Learning Model On Google Cloud Platform (App Engine)
Abhishek Thakur
55 Pair Programming: Deep Learning Model For Drug Classification With Andrey Lukyanenko
Pair Programming: Deep Learning Model For Drug Classification With Andrey Lukyanenko
Abhishek Thakur
56 VS Code (codeserver) on Google Colab / Kaggle / Anywhere
VS Code (codeserver) on Google Colab / Kaggle / Anywhere
Abhishek Thakur
57 Talks # 11: Jean-François Puget; Did you know GPUs are not just for Deep Learning?
Talks # 11: Jean-François Puget; Did you know GPUs are not just for Deep Learning?
Abhishek Thakur
58 End-to-End: Automated Hyperparameter Tuning For Deep Neural Networks
End-to-End: Automated Hyperparameter Tuning For Deep Neural Networks
Abhishek Thakur
59 Deploy Any Machine Learning (or Deep Learning) Endpoint on Google Cloud Platform In 10 minutes
Deploy Any Machine Learning (or Deep Learning) Endpoint on Google Cloud Platform In 10 minutes
Abhishek Thakur
60 Ensembling, Blending & Stacking
Ensembling, Blending & Stacking
Abhishek Thakur

The video introduces GitHub's Codespaces, a cloud-based development environment that allows users to code in the browser, and demonstrates its features such as instant development environment, Visual Studio Code experience, and live sharing collaboration. The video showcases how to configure a Python environment, install extensions, and use Git commands in Codespaces.

Key Takeaways
  1. Create a new Codespace
  2. Configure a Python environment
  3. Install extensions such as Pylint and TQDM
  4. Use Git commands to manage changes
  5. Collaborate with others using live sharing
💡 GitHub's Codespaces provides a cloud-based development environment that allows users to code in the browser, making it easy to collaborate with others and manage projects without the need for local machine setup.

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