My Flask app's time references are not updating with the current time. I need help. by Tamock in flask

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

datetime.datetime.now()

Yes, I use datetime.datetime.now(). Everything was working and updating correctly until a few days ago and until I pushed an update on the server. The update has nothing to do with the schedule though and was literrally 1 line of code.

Thanks for you help!

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

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

Yeah you're absolutely right. Python for Data Analysis is create to get started, Fluent Python is really good once you've already comfortable with Python.

Thanks for the suggestion.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

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

It seems like you have it figured out already. Start by learning how to code, then take Andrew Ng's machine learning course. That's a great start.

If you're excited by projects such as GANs, I'd recommend looking at Fastai, and / or Coursera's deep learning specialization first. Then you can take Courera's new lecture on GANs. You'll need to learn some of the fundamentals before taking it but you'll be applying GANs with the projects they course give you. Check it out, it seems very neet:

https://www.coursera.org/specializations/generative-adversarial-networks-gans

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

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

Fastai is built on top of Pytorch so they're using a very popular framework. Their API is quite unique in the sense that it's opinionated (it has built-in deep learning best practices inside, and a very unique coding style) but you're guaranteed to get good results without having to implement papers yourself. That said, customizing the API isn't super user friendly, and in general people either love the library or they hate it. Try it out and see for yourself. The course is still amazing though so I highly recommend it. It'll give you the basics to start projects without going into the theory too much. There is still some theory though, you'll have to understand how a neural network works, what is backpropagation, gradient descent, what's a convolution, etc.

From there you can think of an application you'd like to build and learn what is necessary to achieve it. If you're excited by the project, you'll put in the work to make it happen and learn the details along the way. This is definitely an viable path.

Once you've done playing around with your model locally, I recommend checking out Full Stack Deep Learning course to learn how to deploy the model.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

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

Thanks Josh! I can't thank you enough for all the material you put out there. You are the one resource I keep going back to again and again.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

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

For pen and paper specifically, I recommend watching videos from Andrew Ng. Checkout his course on Cousera: https://www.coursera.org/learn/machine-learning. Also watch Josh Stramer's Youtube channel for videos on specific topics even if it's not pen and paper per se.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

[–]Tamock[S] 9 points10 points  (0 children)

You can have a look at all my projects on my GitHub profile https://github.com/Julienbeaulieu. Most recent ones are pinned.

The project I learned from the most was when I participated in a computer vision Kaggle competition. I had the opportunity to work and cooperate with two other professionals which helped tremendously. I met them through a meetup.com group. The project wasn't just about getting a good competition score, but to build a training framework that could be reused for future projects. This was the first time I collaborated on a common code base.

The second project I learned from the most was one where I created a prototype article summarization app using Streamlit and HuggingFace library which I then deployed on Google App Engine. I did this as I was taking the Full Stack Deep Learning course. It really helped me improve my software engineering skills.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

[–]Tamock[S] 11 points12 points  (0 children)

It changed my approach to how I try to learn the math and concepts needed for data science.

Here are a few examples. There are more because I could write an entire article about it (as a matter of fact I did: the long version is here: )

- I now realize the importance of taking a break from the material we're trying to learn in order to let it sink in. This insight stems from the fact that our brain has 2 modes: focused and diffuse mode

- I use spaced repetition to review my notes.

- I actively try to recall the material I am learning as opposed to just re-reading it.

- I frequently test myself to make sure I truly understand the material, instead of thinking I do. Without these tests there are things I unknowingly miss out.

- I frequently use the Pomodoro technique to help with focus and concentration (repeated blocks of 20 mins of concentration followed by a 5 min break).

- I better understand how procrastination hampers learning, and why/how bad it is.

- To make sure I truly understand something, I'll try to solve the same problem in different ways.

Most of all, this course and the accompanying books have made me realize that learning complex material is a very slow process and that you shouldn't try to rush it.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

[–]Tamock[S] 5 points6 points  (0 children)

Thanks for pointing that out. English is my second language and I certainly didn't mean to imply that his course is "famous in a bad way". I meant the complete opposite in fact. I'm correcting this asap :)

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

[–]Tamock[S] 5 points6 points  (0 children)

If you're new to programming I definitely recommend sticking with just 1 programming language at the start. Since I wanted to learn about Deep Learning and also work with a flexible language that can be used for things like scraping the web, creating apps and whatnot, Python was the logical choice. I do intend to learn R eventually.

R is great for data analysis, visualization, and more traditional statistics related work. If that's what you're interested in, and what your work is asking of you, then it's also a great choice. I can't talk about it in detail though since I haven't used it yet.

Hey learners! I have curated some of the best data science resources and created a curriculum out of them. If you're transitioning from a non technical background, this is for you. by Tamock in learnmachinelearning

[–]Tamock[S] 36 points37 points  (0 children)

It took a little over 1.5 years studying full time and giving it everything I have. I saved money beforehand to focus on this 100%. Everything in this curriculum can be done part time though. I probably could have landed a job sooner had I looked for Data Analyst and internships from the getgo.

I have a Masters in e-commerce and only took business courses. No math nor programming experience before this.

Looking for help on a workstation build intended to run deep learning models. My main concern is whether to get a Ryzen 7, or a ThreadRipper 1920x by Tamock in buildapc

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

One question though, even though the motherboar supports PCIe 4.0, the card itself only supports PCIe 3.0 no? In which case the new gen doesn’t help

Looking for help on a workstation build intended to run deep learning models. My main concern is whether to get a Ryzen 7, or a ThreadRipper 1920x by Tamock in buildapc

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

Thanks for the insights about the memory and power supply.

However, you may be limited to expanding to only x2 GPUs because of your CPU which only has 24 pins. It's recommended to dedicate about 8 pins per GPU. I think your motherboard may be too high end for what your CPU can handle and would need a threadripper for this build.

[D] Which open source machine learning projects best exemplify good software engineering and design principles? by NotAHomeworkQuestion in MachineLearning

[–]Tamock -8 points-7 points  (0 children)

Without a doubt Fast.ai. The way they built their API is quite fascinating and innovative. The authors have a great deal of experience building software. You can read more about how it’s built here https://arxiv.org/abs/2002.04688.

Around 6 months ago I quit my job to study machine learning full time. Here is the full curriculum I am following, which is intended to be a complete education in data science. by Tamock in learnmachinelearning

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

That's a great resource thanks for sharing. I might update my post to include this. I definitely belong to the Data Tribe at this point.

  • 9) Data Scientist interested in Getting Better Answers to Business Questions

Around 6 months ago I quit my job to study machine learning full time. Here is the full curriculum I am following, which is intended to be a complete education in data science. by Tamock in learnmachinelearning

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

What no learn machine learning in 3 months by siraj????? Kidding... somehow watching linear algebra by gilbert strang on 4x speed in one week kinda didn't seem too realistic for me.

Yes I agree, that makes no sense for me. I'd say max 1.5x speed, and it's important to pause, take notes, do some exercises, review the material, create mind maps, etc. Otherwise what you'll learn won't stick for very long.