#Machinelearning

Is TensorFlow relevant in 2026? Yes, but its role has changed.

The current distribution is as follows:
PyTorch dominates research and GenAI (over 85% of new articles/LLMs).

TensorFlow remains the industry backbone for enterprise deployment and edge AI (TFX, TF Lite).

The innovation is Keras 3, which bridges the gap by allowing code to run on JAX, PyTorch, or TF backends.

Learn PyTorch to invent and learn TensorFlow to deploy at scale. But it's still relevant!

#AI #MachineLearning #TensorFlow2026 #DataScience

Do you really know what generative AI is?

Generative AI is a type of artificial intelligence designed to create new content rather than simply analyzing or classifying data. Instead of simply recognizing patterns, it generates text, images, music, code, voice, or even videos that never existed before, even if they are inspired by training data. #ai #innovation #MachineLearning

When two models share the same accuracy but differ in confidence, choosing the overconfident one can be risky. Modern neural networks often output inflated probabilities, making decisions unreliable. Calibration reveals whether a model’s confidence matches real outcomes. If probabilities matter and both models perform equally, the better calibrated model is the safer choice.
#ai #MachineLearning

Stanford introduced a simple prompting trick that boosts LLM creativity without retraining. Adding a short verbalized-sampling cue makes the model surface multiple possibilities instead of collapsing into predictable answers caused by alignment and typicality bias. By asking for a distribution, not a single reply, the model recovers much of its lost diversity and generates richer outputs.
#LLM #AIResearch #GenerativeAI #PromptEngineering #MachineLearning #ModelAlignment

My go-to Python toolkit I install on EVERY new machine for instant data science superpowers:

1. Jupyter/IPython
2. Mamba (blazing envs)
3. NumPy
4. SciPy
5. SymPy (symbolic math)
6. pandas
7. seaborn
8. Pingouin (easy stats tests)
9. statsmodels (R-like models)

From notebooks to regression in minutes 🚀

#Python #DataScience #MachineLearning #NumPy #Pandas #DataAnalysis