and with larger data sets being able to pinpoint things easily by some easy number is pretty convenient
i cant speak on this more though since i havent done numpy pandas linspace matlab whatever in FOREVER and i personally preferred doing it by hand bc i hate myself and love math
i cant speak on this more though since i havent done numpy pandas linspace matlab whatever in FOREVER and i personally preferred doing it by hand bc i hate myself and love math
September 26, 2026 at 8:52 PM
and with larger data sets being able to pinpoint things easily by some easy number is pretty convenient
i cant speak on this more though since i havent done numpy pandas linspace matlab whatever in FOREVER and i personally preferred doing it by hand bc i hate myself and love math
i cant speak on this more though since i havent done numpy pandas linspace matlab whatever in FOREVER and i personally preferred doing it by hand bc i hate myself and love math
pyhtonがこんだけ出て来たのって
触りやすいし、何より機械学習に向いてるライブラリが豊富だから…よね？:blobcatthinking:
これ、他の言語でもNumpyとかScikit-learnみたいなライブラリあったらどうなんだろ…？:blobcat:
触りやすいし、何より機械学習に向いてるライブラリが豊富だから…よね？:blobcatthinking:
これ、他の言語でもNumpyとかScikit-learnみたいなライブラリあったらどうなんだろ…？:blobcat:
September 26, 2026 at 7:46 PM
pyhtonがこんだけ出て来たのって
触りやすいし、何より機械学習に向いてるライブラリが豊富だから…よね？:blobcatthinking:
これ、他の言語でもNumpyとかScikit-learnみたいなライブラリあったらどうなんだろ…？:blobcat:
触りやすいし、何より機械学習に向いてるライブラリが豊富だから…よね？:blobcatthinking:
これ、他の言語でもNumpyとかScikit-learnみたいなライブラリあったらどうなんだろ…？:blobcat:
📰 Reddit r/MachineLearning
[P] A small MLP from scratch in NumPy with a GUI to look inside it while it trains (weight distributions, t-SNE per layer, neuron ablation...) [P]
https://www.reddit.com/r/MachineLearning/comments/1wqy1qd/p_a_small_mlp_from_scratch_in_numpy_with_a_gui_to#IA##AI##ML#ML
[P] A small MLP from scratch in NumPy with a GUI to look inside it while it trains (weight distributions, t-SNE per layer, neuron ablation...) [P]
https://www.reddit.com/r/MachineLearning/comments/1wqy1qd/p_a_small_mlp_from_scratch_in_numpy_with_a_gui_to#IA##AI##ML#ML
September 26, 2026 at 7:01 PM
📰 Reddit r/MachineLearning
[P] A small MLP from scratch in NumPy with a GUI to look inside it while it trains (weight distributions, t-SNE per layer, neuron ablation...) [P]
https://www.reddit.com/r/MachineLearning/comments/1wqy1qd/p_a_small_mlp_from_scratch_in_numpy_with_a_gui_to#IA##AI##ML#ML
[P] A small MLP from scratch in NumPy with a GUI to look inside it while it trains (weight distributions, t-SNE per layer, neuron ablation...) [P]
https://www.reddit.com/r/MachineLearning/comments/1wqy1qd/p_a_small_mlp_from_scratch_in_numpy_with_a_gui_to#IA##AI##ML#ML
Master the Central Limit Theorem (CLT) with this comprehensive guide #CentralLimitTheorem #Statistics #DataAnalytics #DataScience #Probability #Inference #BSStatistics #LearnDataAnalytics #STEMEducation #DataScienceStudents #ITFeature #Python #DataVisualization #Numpy #Matplotlib #Seaborn
Central Limit Theorem
The central limit theorem states that given a distribution with a mean $\mu$ and variance $s^2$, the sampling distribution of the mean approaches a normal distribution with a mean ($\mu$) and a variance $\frac{s^2}{n}$ as '$n$', the sample size, increases. The amazing thing about the central limit theorem is that no matter what the shape of the original distribution, the sampling distribution of the mean approaches a normal distribution. Furthermore, for most distributions, a normal distribution is approached very quickly as '$n$' increases. What is the Central Limit Theorem? CLT Statement and Formula…
itfeature.com
September 26, 2026 at 5:12 PM
Master the Central Limit Theorem (CLT) with this comprehensive guide #CentralLimitTheorem #Statistics #DataAnalytics #DataScience #Probability #Inference #BSStatistics #LearnDataAnalytics #STEMEducation #DataScienceStudents #ITFeature #Python #DataVisualization #Numpy #Matplotlib #Seaborn
the funny part is every language already solved this by naming it "prefix sum" or "scan". matlab and excel just refused to update and now everyone inherits the joke. numpy even went with cumsum *and* cumprod, so the abbreviation isn't even saving keystrokes anymore.
September 26, 2026 at 3:23 PM
the funny part is every language already solved this by naming it "prefix sum" or "scan". matlab and excel just refused to update and now everyone inherits the joke. numpy even went with cumsum *and* cumprod, so the abbreviation isn't even saving keystrokes anymore.
The last mile of a long road: faster NumPy in the browser
NumPy in the browser now uses OpenBLAS through Emscripten-forge, accelerating matrix multiplication by up to 30.92× for float32 and 14.90× for float64 in the authors’ 1024×1024 benchma…
https://notebook.link/blog/the-last-mile-faster-numpy/
NumPy in the browser now uses OpenBLAS through Emscripten-forge, accelerating matrix multiplication by up to 30.92× for float32 and 14.90× for float64 in the authors’ 1024×1024 benchma…
https://notebook.link/blog/the-last-mile-faster-numpy/
September 26, 2026 at 10:15 AM
The last mile of a long road: faster NumPy in the browser
NumPy in the browser now uses OpenBLAS through Emscripten-forge, accelerating matrix multiplication by up to 30.92× for float32 and 14.90× for float64 in the authors’ 1024×1024 benchma…
https://notebook.link/blog/the-last-mile-faster-numpy/
NumPy in the browser now uses OpenBLAS through Emscripten-forge, accelerating matrix multiplication by up to 30.92× for float32 and 14.90× for float64 in the authors’ 1024×1024 benchma…
https://notebook.link/blog/the-last-mile-faster-numpy/
現場で使える!Python科学技術計算入門 NumPy/SymPy/SciPy/pandasによる数値計算・データ処理手法 (かくあき) が、紀伊國屋電子書籍の【出版社合同】秋のIT書フェア2026で1760円引きの、1760円(50%OFF)+16ポイント還元になりました。10/8(木)まで。
現場で使える！Python科学技術計算入門 NumPy/SymPy/SciPy/pandasによる数値計算・データ処理手法
著者：かくあき(著) 出版：翔泳社 2020/5/19(火)配信
5leaf.jp
September 26, 2026 at 7:13 AM
現場で使える!Python科学技術計算入門 NumPy/SymPy/SciPy/pandasによる数値計算・データ処理手法 (かくあき) が、紀伊國屋電子書籍の【出版社合同】秋のIT書フェア2026で1760円引きの、1760円(50%OFF)+16ポイント還元になりました。10/8(木)まで。
Machine Learning with Numpy! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode
geni.us/M-Learning-N...
geni.us/M-Learning-N...
September 26, 2026 at 2:42 AM
I’m building my way into AI Engineering. 🤖
FastAPI, NumPy & Pandas are getting stronger.
Next target: ML + Deep Learning.
This is just the beginning. 🚀
#AI #MachineLearning #Python #AIEngineering
FastAPI, NumPy & Pandas are getting stronger.
Next target: ML + Deep Learning.
This is just the beginning. 🚀
#AI #MachineLearning #Python #AIEngineering
September 25, 2026 at 5:42 PM
I’m building my way into AI Engineering. 🤖
FastAPI, NumPy & Pandas are getting stronger.
Next target: ML + Deep Learning.
This is just the beginning. 🚀
#AI #MachineLearning #Python #AIEngineering
FastAPI, NumPy & Pandas are getting stronger.
Next target: ML + Deep Learning.
This is just the beginning. 🚀
#AI #MachineLearning #Python #AIEngineering
Authors published a paper in Biorxiv, they used NumPy in the study. Including #RRIDs will make this less ambiguous.
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #methodsmatter #RRID
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #methodsmatter #RRID
www.biorxiv.org
September 25, 2026 at 12:00 PM
Authors published a paper in Biorxiv, they used NumPy in the study. Including #RRIDs will make this less ambiguous.
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #methodsmatter #RRID
SciScore made a table with this resource, see “Automated Services” module (download as csv, xml or #jats) #methodsmatter #RRID
I am once again asking if anyone is in need of a programmer.
I have a lot of experience in data engineering in python, java, and sql. With technologies I've used being spring boot/data/batch, numpy, pandas, pyspark, and the Databricks platform.
I am flexible and can learn technologies quickly
I have a lot of experience in data engineering in python, java, and sql. With technologies I've used being spring boot/data/batch, numpy, pandas, pyspark, and the Databricks platform.
I am flexible and can learn technologies quickly
September 25, 2026 at 9:42 AM
I am once again asking if anyone is in need of a programmer.
I have a lot of experience in data engineering in python, java, and sql. With technologies I've used being spring boot/data/batch, numpy, pandas, pyspark, and the Databricks platform.
I am flexible and can learn technologies quickly
I have a lot of experience in data engineering in python, java, and sql. With technologies I've used being spring boot/data/batch, numpy, pandas, pyspark, and the Databricks platform.
I am flexible and can learn technologies quickly
Finished Module 1 of ML Zoomcamp 2026! 🎉 ML vs rule-based, CRISP-DM, & NumPy/Pandas.
✨ Takeaway: ML is a lifecycle—business & data prep matter most.
🤔 Best part: Shifting from coding rules to letting data find them via vectorization!
➡️ Next: Regression!
#mlzoomcamp @alexeygrigorev.bsky.social
✨ Takeaway: ML is a lifecycle—business & data prep matter most.
🤔 Best part: Shifting from coding rules to letting data find them via vectorization!
➡️ Next: Regression!
#mlzoomcamp @alexeygrigorev.bsky.social
September 25, 2026 at 6:43 AM
Finished Module 1 of ML Zoomcamp 2026! 🎉 ML vs rule-based, CRISP-DM, & NumPy/Pandas.
✨ Takeaway: ML is a lifecycle—business & data prep matter most.
🤔 Best part: Shifting from coding rules to letting data find them via vectorization!
➡️ Next: Regression!
#mlzoomcamp @alexeygrigorev.bsky.social
✨ Takeaway: ML is a lifecycle—business & data prep matter most.
🤔 Best part: Shifting from coding rules to letting data find them via vectorization!
➡️ Next: Regression!
#mlzoomcamp @alexeygrigorev.bsky.social
Season 1 Lesson 43 Part 8 - Your First Steps in Python Numpy Arrays Dimensions 0D to 3D #softwarengineer #learncoding #softwaredeveloper #machinelearning #dataengineer #vibecoding #azure #pythonprogramming #aws #codingtutorial #datascience #pythoncode #jupyternotebook #python #gcp #dataanalysis
September 25, 2026 at 5:15 AM
Season 1 Lesson 43 Part 8 - Your First Steps in Python Numpy Arrays Dimensions 0D to 3D #softwarengineer #learncoding #softwaredeveloper #machinelearning #dataengineer #vibecoding #azure #pythonprogramming #aws #codingtutorial #datascience #pythoncode #jupyternotebook #python #gcp #dataanalysis
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
September 24, 2026 at 10:35 PM
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
September 24, 2026 at 9:50 PM
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
September 24, 2026 at 9:35 PM
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
September 24, 2026 at 9:05 PM
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
I think I'm going to create a new programming language with python, mypy, numpy & multiprocess one day, & make it a hierarchical compiler design, with some very sophisticated compiler heuristics that can be considered a bit "cutting edge" (at least "cutting edge" for it's time anyway).
September 24, 2026 at 7:38 PM
I think I'm going to create a new programming language with python, mypy, numpy & multiprocess one day, & make it a hierarchical compiler design, with some very sophisticated compiler heuristics that can be considered a bit "cutting edge" (at least "cutting edge" for it's time anyway).
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
September 24, 2026 at 7:50 PM
Open Geospatial Solutions - Intro to GIS Programming | Week 6: Introduction to NumPy and Pandas by Author Unknown
https://www.youtube.com/watch?v=Q8LGjEx-jYc
https://www.youtube.com/watch?v=Q8LGjEx-jYc
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers.
Telegram AI Digest
#ai #anthropic #numpy
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers.
Telegram AI Digest
#ai #anthropic #numpy
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers.
towardsdatascience.com
September 24, 2026 at 12:51 PM
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers.
Telegram AI Digest
#ai #anthropic #numpy
Reproducing Anthropic's "Toy Models of Superposition" from scratch in NumPy, with hand-derived gradients and no borrowed numbers.
Telegram AI Digest
#ai #anthropic #numpy
Я обучил крошечную сеть сжимать данные. Она нарисовала пятиугольник.
Воспроизведение "Toy Models of Superposition" от Anthropic с нуля на NumPy, с выведенными вручную градиентами и без заимствованных чисел.
Telegram ИИ Дайджест
#ai #news
Воспроизведение "Toy Models of Superposition" от Anthropic с нуля на NumPy, с выведенными вручную градиентами и без заимствованных чисел.
Telegram ИИ Дайджест
#ai #news
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.
towardsdatascience.com
September 24, 2026 at 12:42 PM
Я обучил крошечную сеть сжимать данные. Она нарисовала пятиугольник.
Воспроизведение "Toy Models of Superposition" от Anthropic с нуля на NumPy, с выведенными вручную градиентами и без заимствованных чисел.
Telegram ИИ Дайджест
#ai #news
Воспроизведение "Toy Models of Superposition" от Anthropic с нуля на NumPy, с выведенными вручную градиентами и без заимствованных чисел.
Telegram ИИ Дайджест
#ai #news