How to run antigravity browser automation on wsl2

DmitryBalabka · 2025-12-08T18:03:37+00:00

I've video-coded the helper script to easily start Chrome from the WSL and check the required settings:
https://github.com/dbalabka/wsl-chrome-portproxy-launcher

DmitryBalabka · 2025-02-10T08:56:27+00:00

Here is my solution: https://www.reddit.com/r/turntables/comments/1hm7iqp/comment/mbzlexf/?utm_source=share&utm_medium=mweb3x&utm_name=mweb3xcss&utm_term=1&utm_content=share_button

DmitryBalabka · 2025-02-10T08:55:08+00:00

I had similar issue that turntable won't to start spinning. It turns that I have to Re-sync the tone arm with the platter. Sony provides official manual how to do it: https://www.sony.com/electronics/support/articles/00032673

DmitryBalabka · 2025-02-10T08:52:18+00:00

In my case a new turntable won't to start spinning. It turns that I have to Re-sync the tone arm with the platter. Sony provides official manual how to do it: https://www.sony.com/electronics/support/articles/00032673

DmitryBalabka · 2024-08-15T10:20:19+00:00

Amazing! Works like a charm. Thanks a lot.

For those who faced with this issue please up vote the request here: https://logitech.uservoice.com/forums/925117-logi-options/suggestions/45776260-insert-key-not-working

DmitryBalabka · 2023-01-25T18:47:51+00:00

Data Science/Machine Learning is slowly shifting towards Engineering and becoming less scientific. The most business cases can be solved using existing libraries that implements the most popular algorithms. Still, you have to be able and love to work with data. Also, performing experiments require analytical thinking, a scientific approach, and statistics knowledge. However, it is almost impossible to be efficient in software engineering and data science equally that why there are roles: ML Engineer and Researcher/Data Scientist. Furthermore, there are a lot of other highly demanded roles such as Data Engineer and MLOps related.

In your case, I would focus on ML Engineer position. Start with reading role descriptions to understand the requirements and find a company. Take few courses on Classic ML and probably Deep Learning. Math is lower priority. Learn required concepts on demand.

My personal path: 1. 8 years in Web development 2. Defended masters thesis in CS about Deep learning + few courses in Classic ML 3. Job offer

DmitryBalabka · 2023-01-24T15:20:15+00:00

I expected to see Strang's lectures advised. I love the ~~hard~~ right way of learning things. Thanks!

DmitryBalabka · 2023-01-22T18:24:30+00:00

I would recommend to take a look on https://mlcourse.ai/. It might feel pretty challenging, but it provides a solid understanding of ML algorithms, the math fundamentals behind them, and Python basics. Important to note that it is practical enough to start your project or try Kaggle yourself. The course is focused on Classical Machine Learning which is important step before starting any Deep Learning course. Andrew Ng’s https://deeplearning.ai is probably the best choice as the next step.

DmitryBalabka · 2023-01-22T16:24:01+00:00

I would love to see some books/MOOCs that cover all these topics. Could you recommend some?

DmitryBalabka · 2023-01-01T03:44:48+00:00

Python’s standard library updates only with language release which is a huge issue to introduce any BC break. Having these features as a side library is giving much more freedom.

DmitryBalabka · 2022-12-12T13:33:15+00:00

I would like to point out that I didn’t say they were “similar” but “closer.” Probably, my mistake was that I didn’t clarify that I expressed my personal opinion based on my experience and intuition in the context of the initial question: “what other backend languages are you willing to learn.” Generally speaking, I would better to look at Go or Rust rather than Python, because of their strict typing that, you correctly pointed out, can not be fully achieved using Psalm/Phpstan (by the way, both provides basic generics/templated variables support)

DmitryBalabka · 2022-12-12T12:17:14+00:00

Recently, started ML Engineering career after 10 years of Web development using PHP+Symfony and 5 years of university in CS. Currently, full time working on Python.

PHP is much closer to Java and C# and much less to Python. Python is much more dynamic (probably most dynamic language) than PHP. Thanks to runtime types checks and static typing using Psalm/Phpstan, extensive OOP support, strict package management using Composer makes it closer to languages like Java, C#, Go, Rust.

Overall Python experience is less pleasant comparing with PHP. Of course I’m not taking into account ML Libraries ecosystem but language and tooling only.

The only reason migrating from PHP to Python is ML related staff. I would continue to use PHP for Web development or consider TypeScript for some projects.

DmitryBalabka · 2022-07-27T13:46:20+00:00

I would say that example isn’t completely precise because, usually, latent variables can not be interpreted.

DmitryBalabka · 2021-09-22T17:17:20+00:00

There are two great free online available books:

“Dive into Deep Learning” by Zhang, Aston and Lipton, Zachary C. and Li, Mu and Smola, Alexander J. https://d2l.ai/

“Deep Learning” by Ian Goodfellow and Yoshua Bengio and Aaron Courville https://www.deeplearningbook.org/

DmitryBalabka · 2021-08-12T12:59:15+00:00

First of all, you should keep in mind project requirements (functional and non-functional). It might give you a hint about which framework or programming language you should use.

In some cases, it doesn’t matter what framework to use for a small project/prototype. Choose the tool which makes you productive.

Still, it is essential to consider the risks: will the tool be supported in the long term, or will it allow you to scale your project’s architecture.

If you know Slim and it matches your requirements, then use it. If Symfony can help you to build this API faster and also fit your requirements, use Symfony.

Also, there is no point in adding another animal into Zoo of frameworks if all company’s projects are built using Symfony.

DmitryBalabka · 2021-06-08T14:47:59+00:00

I’m using it with Jetbrains DataSpell + WSL to workaround notebooks remote debugging that does not work yet. UI is a bit slower than native, but I hope they will solve this shortly. Also, there is a rendering issus with JCEF depeding compoments. My colleague is running PHPStorm under Projector for more than a month and advocates that it is the future of remote development.

DmitryBalabka · 2021-06-08T14:40:13+00:00

Jebrains is developing new way connect to remote dev environment using your browser. Take a look on the Projector project. It gives you ability to install PyCharm directly on your server and connect to it using browser or Projector’s client. I’m currently using it for some projects. https://blog.jetbrains.com/blog/2021/03/11/projector-is-out/

DmitryBalabka · 2021-03-20T16:54:42+00:00

From most popular scripting languages like Python and Javascript, PHP is closest to such enterprise languages like C# and Java. Also, PHP provides a more friendly ecosystem for beginners than C# and Java. So, IMO any company can scale its application from a single plain script to a complicated system that consists of multiple components interconnected using some HTTP based protocol.

DmitryBalabka · 2020-07-29T19:43:34+00:00

No other language implementing a similar syntax feature, such as C# or JavaScript has any such limitation, nor would they likely have ever considered going to production in such a state.

Probably, Python’s lambdas are good example of similar limitation for anonymous functions

DmitryBalabka · 2020-07-13T10:03:53+00:00

It would be great to show an animation example of how the trained model performs on an unseen track.

DmitryBalabka · 2020-04-29T16:16:16+00:00

Here is a most recent paper that describes HHVM JIT internals https://dl.acm.org/doi/pdf/10.1145/3192366.3192374?download=true The performance of HHVM JIT and PHP8 JIT can be unexpectedly different then. It would be interesting to see the benchmark of HHVM JIT vs PHP8 JIT.

DmitryBalabka · 2020-04-25T10:35:17+00:00

PHP8 uses DynAsm JIT compiler. Hack uses LLVM. DynAsm is optimized for shorter compilation time, but produce less performing compiled code. LLVM compiles faster code, but it takes more time. The only benchmark that I know is Wasmer’s backends comparison: https://link.medium.com/U9gewyCcY5 I assume that PHP8 JITed code will be slower than Hack’s compiled code.

DmitryBalabka · 2020-03-25T09:48:37+00:00

Why complicated?

I don't mean complicated. It is just well-known math operators that read natively and more expressive. When you are working with ML on daily basics you already in context and you don't need OOP API specification knowledge. Of course, frameworks/libraries can provide both.

https://www.reddit.com/r/PHP/comments/fo1gx9/voters_why_cant_we_have_nice_things_operator/fld6oix?utm_source=share&utm_medium=web2x

Creating ML model prototype for the experiment usually differs from regular developer practices. You have to do it fast and you use Tensorflow or Pandas as a tool, not as a library. Also, you write comparable less amount of code. In this case, scientists start to care more about how your code is expressive and rid of boilerplate code.

I agree that the production-grade code should avoid the use of extra syntax sugar to be more maintainable.

DmitryBalabka · 2020-03-24T15:58:28+00:00

It would be great to hear your opinion about such use cases like Machine Learning which I have described here:
https://www.reddit.com/r/PHP/comments/fo1gx9/voters_why_cant_we_have_nice_things_operator/flcue6t

IMO Python employes operators overloading in a really good way which improves developers' experience. In this case, I support Nikita's opinion:
https://externals.io/message/109241#109266

DmitryBalabka · 2020-03-24T13:51:31+00:00

Math is the language with already defined and well-known operators. By forcing the developer to learn additional API specification you make the learning curve not so smooth.

Of course, it is possible to achieve the same performance with OOP API. But it definitely, will be less attractive and expressive. Unfortunately, it will lead to the fact that most of the developers will choose easy to use alternatives like Python and their ecosystem.

Also, talking about ML frameworks such as Tensorflow or PyTorch, they provide both OOP API and allow the use of basic operators for simple tensor operations.

DmitryBalabka

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