01.04.2025 /R
Intro to QML, pt. 401.04.2025 /R
Intro to QML, pt. 301.04.2025 /R
Intro to QML, pt. 201.04.2025 /R
Intro to QML, pt. 101.04.2025 /R
Quantum algorithms01.04.2025 /R
Intro to quantum computing01.04.2025 /R
Swarm intelligence01.04.2025 /R
Spiking neural network01.04.2025 /R
Everybody needs a dashboard01.04.2025 /R
Basics of BI01.04.2025 /R
Introduction to data analytics01.04.2025 /R
Experimental design01.04.2025 /R
Data visualization26.03.2025 /R
Approximate inference21.03.2025 /R
Basics of prompting18.03.2025 /R
MoE architecture13.03.2025 /R
Deploying LLMs06.03.2025 /R
LLM inference optimization25.02.2025 /R
Advanced RAG20.02.2025 /R
RAG for LLMs19.02.2025 /R
LLM engineering14.02.2025 /R
Intro to AI engineering10.02.2025 /R
Vector databases & ANN04.02.2025 /R
Causal representation learning25.01.2025 /R
Graphical models16.01.2025 /R
Bayesian networks12.01.2025 /R
Partition function (a closer look)16.12.2024 /R
Monte Carlo methods16.12.2024 /R
Sampling, in-depth13.12.2024 /R
Neural ODEs03.12.2024 /R
Deep probabilistic models20.11.2024 /R
Information theory for ML13.11.2024 /R
Group theory for ML, pt. 211.11.2024 /R
Group theory for ML, pt. 106.11.2024 /R
Contrastive learning & SimCLR01.11.2024 /R
Normalizing flows28.10.2024 /R
Adversarial ML17.10.2024 /R
Training models at scale, pt. 214.10.2024 /R
Training models at scale, pt. 110.10.2024 /R
AI reasoning & uncertainty, pt. 210.10.2024 /R
AI reasoning & uncertainty, pt. 109.10.2024 /R
AI planning03.10.2024 /R
Knowledge representation19.09.2024 /R
AI logic19.09.2024 /R
AI search18.09.2024 /R
Synthetic data06.09.2024 /R
Semi-supervised learning22.08.2024 /R
Self-supervised learning15.08.2024 /R
Retrieval-augmented generation09.08.2024 /R
Geometry estimation, pt. 207.08.2024 /R
Geometry estimation, pt. 102.08.2024 /R
AI web agents28.07.2024 /R
Intelligent agents20.07.2024 /R
Federated learning17.07.2024 /R
Econometrics for DS11.07.2024 /R
Contrastive language-image pretraining06.07.2024 /R
Advanced AB-tesing30.06.2024 /R
Multimodal models20.06.2024 /R
Intro to AI theory, pt. 220.06.2024 /R
Intro to AI theory, pt. 105.06.2024 /R
Cloud analytics01.06.2024 /R
AI-driven navigation20.05.2024 /R
Multithreading in ML12.05.2024 /R
Automated ML, pt. 212.05.2024 /R
Automated ML, pt. 109.05.2024 /R
DBN architecture28.04.2024 /R
RvNN architecture27.04.2024 /R
Kernel (in-depth look)22.04.2024 /R
Siamese neural network13.04.2024 /R
Social networks analysis10.04.2024 /R
Active learning26.03.2024 /R
Graph neural networks14.03.2024 /R
Learning to rank04.03.2024 /R
Data engineering zone29.02.2024 /R
Online machine learning14.02.2024 /R
Pose estimation09.02.2024 /R
Music generation03.02.2024 /R
Speech synthesis03.02.2024 /R
Speech recognition21.01.2024 /R
Topic modeling17.01.2024 /R
Depth map15.01.2024 /R
Data collection techniques20.12.2023 /R
PixelRNN & PixelCNN12.12.2023 /R
Inpainting06.12.2023 /R
Image blending24.11.2023 /R
Batch-normalization22.11.2023 /R
Dialogue systems18.11.2023 /R
Optical character recognition07.11.2023 /R
Playing with PySpark02.11.2023 /R
Intro to RL19.10.2023 /R
Image object segmentation16.10.2023 /R
Image object detection13.10.2023 /R
Vision transformers04.10.2023 /R
Tuning LLMs03.10.2023 /R
Intro to LLMs, pt. 201.10.2023 /R
Intro to LLMs, pt. 125.09.2023 /R
Sentence transformer23.09.2023 /R
BERT model12.09.2023 /R
Transformer architecture, pt. 211.09.2023 /R
Transformer architecture, pt. 110.09.2023 /R
Attention mechanism05.09.2023 /R
Diffusion models28.08.2023 /R
SQL and databases for DS14.08.2023 /R
Word embeddings11.08.2023 /R
Intro to NLP04.08.2023 /R
NST algorithm03.08.2023 /R
Img-to-img translation27.07.2023 /R
Recommender systems17.07.2023 /R
Intro to Computer Vision06.07.2023 /R
Hierarchical clustering01.07.2023 /R
Bayesian models22.06.2023 /R
GAN architecture23.06.2023 /R
Energy-based models20.06.2023 /R
Generative models17.06.2023 /R
Autoencoder architecture12.06.2023 /R
RNN architecture08.06.2023 /R
Inception and DenseNet07.06.2023 /R
ResNet architecture25.05.2023 /R
CNN architecture, pt. 224.05.2023 /R
CNN architecture, pt. 115.05.2023 /R
Neural network concepts, pt. 315.05.2023 /R
Neural network concepts, pt. 215.05.2023 /R
Neural network concepts, pt. 109.05.2023 /R
Markov models08.05.2023 /R
Sequential models05.05.2023 /R
Improving ML models25.04.2023 /R
t-SNE21.04.2023 /R
Dimensionality reduction & PCA15.04.2023 /R
Intro to PyTorch01.04.2023 /R
Classification metrics01.04.2023 /R
Clustering metrics26.03.2023 /R
Mean shift22.03.2023 /R
Gaussian mixture models10.03.2023 /R
Gaussian processes04.03.2023 /R
Anomaly detection27.02.2023 /R
Time series19.02.2023 /R
Ensemble methods13.02.2023 /R
Intro to TensorFlow & Keras05.02.2023 /R
Advanced optimizers02.02.2023 /R
Gradient optimization20.01.2023 /R
DBSCAN & OPTICS09.01.2023 /R
Intro to MLOps25.12.2022 /R
Video processing23.12.2022 /R
Image processing14.12.2022 /R
K-nearest neighbors09.12.2022 /R
Intro to Big Data24.11.2022 /R
Association rule learning15.11.2022 /R
Support vector machines08.11.2022 /R
Decision trees02.11.2022 /R
Clustering & K-means27.10.2022 /R
Logistic regression23.10.2022 /R
Regression analysis11.10.2022 /R
Regularization05.10.2022 /R
Linear regression28.09.2022 /R
Exploratory data analysis20.09.2022 /R
ML isn't for kids12.09.2022 /R
Algorithms and data structures07.09.2022 /R
Calculus for ML/DS05.09.2022 /R
Hypothesis testing, pt. 205.09.2022 /R
Hypothesis testing24.08.2022 /R
Statistical distributions23.08.2022 /R
A non-boring intro to statistics, pt. 218.08.2022 /R
A non-boring intro to statistics22.07.2022 /R
Web tools for DS21.07.2022 /R
Linux essentials for DS/ML20.07.2022 /R
CS essentials for DS/ML02.06.2022 /R
Linear algebra for ML29.05.2022 /A
Venturing forth!29.05.2022 /R
On research29.05.2022 /T
Lifelong pilgrimage
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