data science

"The actual data science part is harder to automate, because every problem requires business context and an understanding of how to achieve your goal with the data you have."

"I have been testing every model that comes out, and I can confidently say I’ll be cancelling my cloud subscriptions."

"I’m aiming to land a meaningful internship by July, ideally in AI/ML or data-related roles... I’m not looking for shortcuts—just trying to focus on the right things."

"We found that deferring AI assistance leads to the highest-quality hints. Further, this design helps students identify a wide range of mistakes they otherwise struggle to identify without any AI assistance."

"I know basics of ML models and NLP and have some basic understanding of neural networks. Even if I don’t find a job in this area I want to learn for the sake of gaining knowledge."

"Free tutorial on Machine Learning Projects (End to End) in Apache Spark and Scala with Code and Explanation"

"I find that building and validating Python packages that cover a core area of analytical work that I do and then exposing it to Claude as a skill... gets me 80% of the way of automating a major DS responsibility."

"Has anyone tried Math Academy for learning math? They also have a dedicated course on machine learning math."

"gpt-4.1-mini leads (0.832) — beats GPT-5 at 47× lower cost"

"I want to investigate this by using NLP to describe the incidents, then describe the observations, and see if there is a difference in content."

"The concept of this team is to realize a world where business people and beginners in data science can achieve their desired analysis by leaving specialized analysis and implementation to an AI agent team..."

"Because Keirin is a group battle based on temporary teams (lines) tied by factors like hometown, you cannot predict it without parameterizing 'loyalty, human emotion, and unspoken understandings'."

"機械学習モデルの解釈手法としてSHAP はかなりメジャーな選択肢です。特徴量ごとの寄与をサンプル単位でも全体傾向でも見られるためとりあえず SHAP を見ておく,という場面はかなり多いように思えます。"

"I’m a PhD student in Machine Learning and Computer Vision, and I often help students and developers with Python and ML-related problems."

"I started with Python, learned some Pandas and NumPy, worked with a dataset from Kaggle, and tried Matplotlib (still pretty bad at it 😅)."

"i am a data scientist programmer and clinical psyche using opus 4.6 with chat gpt 5.4 and codex in microsoft vs code fo literally run entirely self autinomous system"

"I would like to apply my自制 horse racing prediction model to the G1 races over the next year and verify its performance."

"In NumPy, four arithmetic operations between arrays can be done intuitively with +, -, *, /. ... Additionally, by using sum() on an array, you can find the sum of all elements within that array, and for 2D arrays and higher, you can specify an axis to perform vertical or horizontal additions."

"In this article, we liken the mechanics of scikit-learn to a weather observatory. Estimator API design philosophy — why all models are unified with fit/predict. Pipeline power — a method to integrate everything from preprocessing to model training into a single flow."

"Disarray凭空跳开的近20分，让一场关于benchmark本质的论战，就此拉开。"

"I think I should spend more time understanding the concepts."

"I’m a fast learner, highly motivated, and eager to work on real-world problems. I’m still exploring the field, so I’d also really appreciate any guidance on what skills or areas I should focus on to improve and contribute better."

"それぞれの役割は次のように整理できます。 AI：知的行動を実現する「目的」 モデリング：現実世界を表現する「前提」 統計：不確実性の中で正しさを定義する「理論」 機械学習：モデルを最適化する「計算手段」"

"I usually deliver around 3 or 4 ML/AI projects each year. I’m also expected to do multiple analyses separate from this so I’m not only focused on ML/AI."

"Data preprocessing is an extremely important process that determines the success or failure of the project... 'Those who rule preprocessing rule machine learning!'"

"I’ve got an onsite coming up with two technical rounds and one behavioral. The recruiter said the technicals could cover DSA, pandas, maybe SQL, live modeling exercises, or even a case study. There might also be some 生成AI knowledge checks."

"What % of roles now require AI skills, broken down by seniority level. Salary premium for candidates with AI skills."

"My goal is to understand and implement ML algorithms, preprocess data, and use libraries like NumPy, Pandas, and scikit-learn."

"AI (Machine Learning) works by: Input + Correct Data → Automatically Learn Rules → Output. For example, if you give a system massive amounts of weather data and 'Hot/Cold' labels, it automatically learns 'what temperature constitutes hot'!"