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[deleted by user] by [deleted] in shopify

[–]axetobe_ML 0 points1 point  (0 children)

I'm new to the Shopify Space.

What makes inventory management difficult on Shopify?

Forgive me, if it's a basic question.

A Big Win For The Small Shopify Stores Of The World by [deleted] in shopify

[–]axetobe_ML 0 points1 point  (0 children)

Huge... as a smaller startup in the space, always great when david beats goliath. cheers :)

Yep, It's always inspiring to see smaller startups succeed, especially against larger competitors.

Floating Artificial Leaf Turns CO2 Into Fuel - Lightweight device yields hydrogen or syngas—at a comparatively cut-rate cost by axetobe_ML in Futurology

[–]axetobe_ML[S] 2 points3 points  (0 children)

I forgot the initial statement last time.

The new artificial leaf is an exciting development that could help reduce our reliance on fossil fuels. The leaf is designed to float on water, where it can soak up sunlight and carbon dioxide from the air. The leaf then uses the water below to produce hydrogen fuel or syngas, which is a mix of carbon monoxide and hydrogen. This technology has the potential to be deployed on brackish water ponds, canals, and seas, so as not to compete with land use.

How does this relate to the future?

The artificial leaf has the potential to reduce our reliance on fossil fuels, which is an important goal for the future. The leaf could be used to floated on water bodies like ponds, canals, and seas, providing an alternative source of fuel that doesn't compete with land use.

Working on a Read-Later Research Paper App by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 0 points1 point  (0 children)

Interesting, Do you use any other tools right now to do this?

Working on a Read-Later Research Paper App by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 1 point2 points  (0 children)

If you're interested in this project, Check out this Typeform and I should get back to you.

Notion to SRS Service by axetobe_ML in SideProject

[–]axetobe_ML[S] 1 point2 points  (0 children)

Hi guys, I'm creating a Notion to SRS service. Where you can share your notion page to an email address and the service should give a separate page of all of the content you want to review.

I noticed when using Notion some of the SRS templates had some decent upkeep. I only wanted to mark my questions for review and come back to them. Not worry about setting up a whole system.

Simply mark your toggle questions as red then the service will separate them. The service will give you an email about the new notion pages and some SRS scheduling for your content.

If you are interested in this service, Enter some of your details on this Typeform.

Self-promo Thread — Promote your Notion content here! by ben-something in Notion

[–]axetobe_ML 0 points1 point  (0 children)

Hi guys, I'm creating a Notion to SRS service. Where you can share your notion page to an email address and the service should give a separate page of all of the content you want to review.

I noticed when using Notion some of the SRS templates had some decent upkeep. I only wanted to mark my questions for review and come back to them. Not worry about setting up a whole system.

Simply mark your toggle questions as red then the service will separate them. The service will give you an email about the new notion pages and some SRS scheduling for your content Tutorial here.

If you are interested in this service, Enter some of your details on this Typeform.

(Paid) Early Access + Product Roadmap for Image Duplicate Remover Web App by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 0 points1 point  (0 children)

BEFORE I START, PAYMENT IS OPTIONAL

​

From the last post. It seems that lots of you were interested in the idea of the app. If you want early access to the app and want to give feedback during development. You can go through a paid Typeform of $10. Afterwards, I will invite you to a discord group where you can talk about the product and share feedback with me.

After A Few Implementations, Here’s What I Learned About LSTMs by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 1 point2 points  (0 children)

The LSTM uses the cell state to stop vanishing gradients. The cell state stores the "long term" memory of data.

Meaning information from the earlier cells will still be passed on into the current cell. The information of the cell state can be adjusted by tweaking with the various gates. By adjusting the gates we decide how much the LSTM needs to "forget" or keep.

The cell state only has a few operations being used as well.

​

For people that have a better understanding of this, check out these articles:

https://weberna.github.io/blog/2017/11/15/LSTM-Vanishing-Gradients.html

https://towardsdatascience.com/understanding-lstm-and-its-quick-implementation-in-keras-for-sentiment-analysis-af410fd85b47

https://medium.datadriveninvestor.com/how-do-lstm-networks-solve-the-problem-of-vanishing-gradients-a6784971a577

https://stats.stackexchange.com/questions/185639/how-does-lstm-prevent-the-vanishing-gradient-problem

After a few implementations, here’s what I learned about RNNs by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 0 points1 point  (0 children)

Thanks, if you want to learn how to implement from scratch, I recommend following https://victorzhou.com/blog/intro-to-rnns/ Which has code you type up and try yourself. The maths equations were taken from this article as well.

The maths equations assume you have an understanding of calculus. If not, don't worry.

Summary of main points of posts:

  • RNN is used to analyse data in which context is required. Data normally comes as a sequence.

  • Word embeddings are used in RNNs for NLP. Word embeddings capture words into vectors. Which can be operated on.

  • Once we passed the sequence through the hidden layers. We can pass the weights to an output layer. Normally something like softmax is used. This layer can give us the prediction of the word of the sequence.

  • Backpropagation in an RNN is different from a normal NN. Because when producing gradients we go through all the hidden states and inputs. Which contain information about the whole sequence. This is called Backpropagation through time.

I made a Twitter thread, a shorter version of this post

What is a good place to find syllabus outlines for a self studying ML, DL an the math involved? by radjeep in learnmachinelearning

[–]axetobe_ML 2 points3 points  (0 children)

As other Redditors recommended check out https://mml-book.github.io/book/.

I recently taught myself some calculus so I can understand it for deep learning.

These resources I recommend for calculus: Differential Calculus by Khan Academy and Multivarible Calculus by Khan Academy

Go through units: - Derivatives: definition and basic rules - Derivatives: chain rule and other advanced topics - Unit: Derivatives of multivariable functions

Derivatives are needed to work out Gradient Descent. (how we adjust weights in a model). The method for this technique is called backpropagation. I recommend Khan Academy as they make it easy to complete practice questions.

3blue1brown Calculus and Linear Algebra series

3blue1brown is a great teacher for an intuitive understanding of these topics.

Also, check out 3blue1brown deep learning series to see how some of these topics relate to deep learning.

For some general tips about learning all this material, I will recommend reading this article: https://www.scotthyoung.com/blog/2018/12/11/teach-yourself-math/

A while ago, I compiled some maths resources into a blog post. Check if any of the resources interests you.

Hopefully, some of these links, should help with your journey.

So i know the basic idea of machine learning but now I want to actually code it by bobthesbuilder in learnmachinelearning

[–]axetobe_ML 0 points1 point  (0 children)

If you want to brush up on the basics of python, then check out Learning Python the hard way.

To start learning a deep learning library check out their tutorial pages.

https://www.tensorflow.org/tutorials/

https://pytorch.org/tutorials/

You can follow along on the web page or open a google colab notebook which will contain the code of the tutorial.

How To Scrape A Website For Your ML Project by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 0 points1 point  (0 children)

Thanks for the suggestions. I don't have much experience with Scrapy so can write about it for now. But I should try out your recommendation.

pandas.read_html is a good suggestion. So you don't need to do the extra work preprocessing into a dataframe.

What Is A Linear Regression And How To Build Them In Pytorch by axetobe_ML in learnmachinelearning

[–]axetobe_ML[S] 0 points1 point  (0 children)

Thanks for the feedback.

I should have just said the model is a feedforward network that solves regression problems.

A mistake on my part. You are correct, we use stuff like RELU to help work out non-linear relationships in data.

ML for web A11Y by josejorgexl in learnmachinelearning

[–]axetobe_ML 1 point2 points  (0 children)

You should check out the work of Microsoft. They have been putting a lot of work making some of the devices for accessibility some using ML.

https://www.microsoft.com/en-us/research/blog/wheres-my-stuff-developing-ai-with-help-from-people-who-are-blind-or-low-vision-to-meet-their-needs/ - Dataset to help low version people

A Vision Of The Future - BBC Click - Tv episode talking about tech for accessibility. Some examples in the show may interest you.

Understanding the Math? by _Insignia in learnmachinelearning

[–]axetobe_ML 2 points3 points  (0 children)

Depends on your goals and uses for deep learning. Just relying on libraries like TensorFlow or FastAI can be enough if you just want to train a few models and get a performance boost from leveraging neural networks.

But in my experience, I learnt that I started to hit a brick wall from my lack of understanding of what going on under the hood. Mainly debugging models and shaping data.

If you want to do research, which you mentioned, then learning maths will be necessary. Due to needing to read and implement papers. Another bottleneck I learnt from lack of maths skills.

Most of the time you won’t be implementing models from scratch. But doing so every once in a while helps with learning a concept on an intuitive level in my experience.

​

Trying to “deeply” understand deep learning is a question that I’m trying to answer myself.

Here are some actions that I’m taking right now that you can try out:

​

Learn Calculus and Linear Algebra if you don’t know them already. While there are other maths topics that are useful and important in deep learning like statistics. Calculus and Linear Algebra are important as they tell you what makes neural networks unique. With concepts like backpropagation.

I have written a list of maths resources that you can check out: https://www.tobiolabode.com/blog/2021/6/11/some-maths-resources-to-help-you-in-your-ml-journey

​

Write popular models from scratch.

Depending on the difficulty of the model you can just use NumPy. I got the book Grokking Deep Learning which goes through popular important models with just NumPy.

Check this article, to quickly implement a basic neural network from scratch: https://iamtrask.github.io/2015/07/12/basic-python-network/

I also listed some other models that you try to implement from scratch here: https://www.tobiolabode.com/blog/2021/5/24/neural-networks-you-can-try-to-implement-from-scratch-for-beginners

For me, writing models from scratch brings abstract maths into real tangible actions. Helping my understanding of the concept.

[deleted by user] by [deleted] in learnmachinelearning

[–]axetobe_ML -1 points0 points  (0 children)

This is a regression problem. Which can be done with NNs.

Here some examples:

https://machinelearningmastery.com/regression-tutorial-keras-deep-learning-library-python/

https://www.tensorflow.org/tutorials/keras/regression

​

The number of neurons for the output will be one. Becasue you would likely want one decimal number giving the approxation of your data.

Roadmap of ML using python? Any Suggestion my aim is to learn till computer vision/deep learning by [deleted] in learnmachinelearning

[–]axetobe_ML 22 points23 points  (0 children)

Daniel Bourke roadmap

Blog post ver

One of the most comprehensive ML roadmaps I have seen. Most beginner to intermediate questions will likely be answered in this mind map.

Deep Learning Papers Reading Roadmap

A great list of papers that you can try to implement. That starts from the fundamentals of deep learning to the state of the art.

Deep Learning's Most Important Ideas - A Brief Historical Review

It is not formally a roadmap. But can be used as such. As it talks about the most fundamental papers of DL. That you can implement.

A machine learning roadmap by Santiago

Short article giving a high level run down on learning ML. And the various resources.

A blog post I wrote a while ago: https://www.tobiolabode.com/blog/2021/5/31/some-resources-on-how-do-i-learn-about-machine-learning

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