Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

Hackers' Guide to Language Models

Concept Sliders for Precise Control of Diffusion Models

Erasing Concepts from Diffusion Models

Unified Concept Editing in Diffusion Models

SliderSpace: Decomposing the Visual Capabilities of Diffusion Models

Distilling Diversity and Control in Diffusion Models

Erasing conceptual knowledge from language models through low-rank fine-tuning