Lesson here, know your fucking audience no?
Source: x.com/BLUECOW009/status/1859010858128732380
Anyone here experienced in making PR to pytorch? I need some guidance
Source: x.com/BLUECOW009/status/1858928376741872092
every male yearns for this
Source: x.com/yacineMTB/status/1858992815822565673
deep learning is a french science
Source: x.com/yacineMTB/status/1858795911486599232
The technical term for this is sycophancy. Appears to get worse the larger the model gets.
Source: x.com/mattpocockuk/status/1858964697879343522
If I were to start Data Science in 2025 from
- Harvard
- Stanford
- MIT
- Microsoft
- IBM
❯ Python ➟ http://cs50.harvard.edu/python/2022/
❯ SQL
http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql…
❯ Excel, PowerBI
http://learn.microsoft.com/training/paths/modern-analytics/…
❯ R
http://cognitiveclass.ai/courses/r-101
❯ Tableau
http://tableau.com/learn/training
❯ PowerBI (Data Analytics)
http://learn.microsoft.com/users/collinschedler-0717/collections/m14nt4rdwnwp04…
❯ Mathematics
http://ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum…
❯ Statistics
https://cognitiveclass.ai/courses/statistics-101-c9adda60-c62d-4962-b5ad-065b9e825bf8…
❯ Linear Algebra
❯ Probability
http://pll.harvard.edu/course/data-science-probability…
❯ Data Analysis
http://pll.harvard.edu/course/data-analysis-life-sciences-4-high-dimensional-data-analysis…
❯ Data Visualization
http://pll.harvard.edu/course/data-science-visualization…
❯ Machine Learning
http://developers.google.com/machine-learning/crash-course…
❯ Deep Learning
http://introtodeeplearning.com
Source: x.com/swapnakpanda/status/1858866223741624705
"We would build a rocket ship and then we'd fly it far away" LFG!
https://video.nostr.build/bf9c8113610d0feb2173cca3bd7fdea2007f3a4c1ecf7cee1f45543b026c7484.mp4
Source: x.com/nfkmobile/status/1858878669973790985
I should try this
Source: x.com/BLUECOW009/status/1858948660823826611
Source: x.com/yacineMTB/status/1858977549701050486
Lmao this is a nightmare. Testing multiple things at once. Thank god I'm in software
Source: x.com/yacineMTB/status/1858924958426296630
Here's my blog, if anyone is interested:
Source: x.com/denicmarko/status/1858889943453499695
A to Z of Data Science
❯ A ➟ Algorithms, Analytics, AI
❯ B ➟ Bayes' Theorem, BigData, Bias
❯ C ➟ Clustering, Classification, Cross Validation
❯ D ➟ Dataset, Dimensionality Reduction
❯ E ➟ EDA, Excel, Ensemble Learning
❯ F ➟ Feature Engineering, Forecasting
❯ G ➟ Gradient Descent
❯ H ➟ Hypothesis, Histogram
❯ I ➟ Imputation
❯ J ➟ Jupyter Notebook, Java
❯ K ➟ K-Means, Kernel, Kaggle
❯ L ➟ Logistic Regression, Linear Regression
❯ M ➟ Mathematics, Machine Learning
❯ N ➟ Normalization, NumPy
❯ O ➟ Outlier, Overfitting, Optimization
❯ P ➟ Python, PowerBI, PyTorch
❯ Q ➟ Quantile
❯ R ➟ Regression, Random Forest
❯ S ➟ SQL, scikit-learn, Supervised Learning
❯ T ➟ TensorFlow, Time Series Analysis
❯ U ➟ Unsupervised Learning, Underfitting
❯ V ➟ Variance, Visualization
❯ W ➟ Weighted Average, Wrangling
❯ X ➟ X-Axis, XML
❯ Y ➟ Yield Curve Analysis, Y-Axis
❯ Z ➟ Z-Score, Zero Padding
Source: x.com/swapnakpanda/status/1858720646827557203
Tomorrow's The Pragmatic Engineer Podcast episode:
How Linear gets so much done, with such a small team.
10,000+ companies use Linear, including 66% of Forbes Top 50 AI companies. They are profitable, full-remote and have 25 engineers.
With Linear's first EM, Sabin Roman.
Source: x.com/GergelyOrosz/status/1858886660131307830
Kash Patel whenever he watches you open a browser in incognito mode.
Source: x.com/TheJackForge/status/1858925441098338765
NEW POST
Last month GitHub Copilot released a new multi-file editing capability: a powerful coding assistance feature which expands the scope of AI assistance to larger changes over many files. Birgitta Böckeler gave it a try.
Source: x.com/martinfowler/status/1858894468998451348
Follow :)
Source: x.com/BLUECOW009/status/1858926796676186426
the way we learn different languages is going to change forever
here's me learning japanese with an audio based assistant
Source: x.com/yacineMTB/status/1858870494159671740
Seems like everyone's number one question with building with AI is "how do you make it not shit?"
The answer is evals. They're like unit tests, but for probabilistic systems.
Here's an imaginary API to explain how they work:
Source: x.com/mattpocockuk/status/1858526867273199924
When the big cheese says he is going to do something it happens. Every single time, it happens. Sometimes a little late but it always happens
Source: x.com/yacineMTB/status/1858839754491547658
Share your websites!
Source: x.com/denicmarko/status/1858851123680960863