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DEV.to
TensorFlowAs a mini-blog, it is a nice alternative for Medium to publish and share information about programming.
However, the community and the organization are biased toward social justice (and they are open to it). You can read its Code of Conduct, it is so vague and politically leads (I prefer a term of service because it defines fair rules for everybody). So it alienates developers that we don't care about politics in pro of people that want to talk about any other topic such as sexuality, how women are unprivileged, and such. It even mandates to use inclusive language. Good grief.
My main complaint is the quality of the community. It is not StackOverflow (so we don't want to ask for an answer here), and most of the top topics are clickbait, such as "how to become a rockstar developer in ... days", "100 tips to become a better programmer" (and it doesn't even talk about programming).
Technically this "mini blog" site allows us to use markdown, and it is okay. However, the whole experience is really basic. Even the template is ugly.
Based on our record, DEV.to seems to be a lot more popular than TensorFlow. While we know about 665 links to DEV.to, we've tracked only 8 mentions of TensorFlow. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is a tiny, silly personality quiz built for the DEV.to Weekend Doggos challenge. Answer questions about your Saturday mornings, your feelings on doorbells, and your ideal compliment โ and find out which dog breed you truly are today. (Not forever. Today. Check back tomorrow, you might be a different dog.). - Source: dev.to / about 5 hours ago
Verifiable only with effort. Anything touching the filesystem, package installs, CI config, database changes. Wrongness here is quiet and expensive. These get the strongest model I have and a sandboxed dry run before anything executes. I wrote a separate piece on dry-running assistant-written shell commands because this category keeps hurting people. - Source: dev.to / 2 days ago
Def _pending_leaves(comment): if not comment["children"]: if comment["user"]["username"] != ME: yield comment return for child in comment["children"]: yield from _pending_leaves(child) Def _pending_entries(comment, drafted_codes): for leaf in _pending_leaves(comment): if leaf["id_code"] in drafted_codes: continue yield { ... - Source: dev.to / 2 days ago
In part 1 I made the pitch: real-time UI in one language, no JavaScript build. Now let's build something and ship it two ways from the same source. - Source: dev.to / 9 days ago
Def pending(): try: drafted_text = open(DRAFTS, encoding="utf-8").read() except FileNotFoundError: drafted_text = "" drafted_codes = set(re.findall(r"^## (\S+)", drafted_text, re.M)) out = [] for a in api(f"/articles?username={ME}&per_page=100"): if not a["comments_count"]: continue for c in api(f"/comments?a_id={a['id']}"): if not... - Source: dev.to / 12 days ago
The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even open-source solutions require technical expertise that many lack. - Source: dev.to / 5 months ago
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 3 years ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: about 4 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 4 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: over 4 years ago
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