Datamlistic

3:15

Hyperparameters Tuning: Grid Search vs Random Search
DataMListic
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4:31

AI Reading List (by Ilya Sutskever) - Part 1
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13K views
4:29

Why Neural Networks Can Learn Any Function | The Universal Approximation Theorem
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9.2K views
2:55

XGBoost Explained in Under 3 Minutes
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30K views
4:23

Bagging vs Boosting - Ensemble Learning In Machine Learning Explained
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60K views
2:44

Word Error Rate (WER) Explained - Measuring the performance of speech recognition systems
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669 views
2:21

Why We Don't Accept The Null Hypothesis
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352 views
0:59

Fourier Transform Maths Explained #fouriertransform #maths #mathematics
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31K views
8:11

LLM Prompt Engineering with Random Sampling: Temperature, Top-k, Top-p
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4.1K views
1:00

Covariance vs correlation #machinelearning #statistics #datascience #deeplearning #maths
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4.8K views
0:52

Attention Mechanism Explained #machinelearning #transformers #deeplearning #datascience #nlp
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1.6K views
0:54

Low-rank adaptation (LoRA) - fine-tune large language models like ChatGPT #machinelearning #chatgpt
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649 views
0:48

XGBoost explained #datascience #machinelearning #statistics #xgboost #decisiontrees
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12K views
0:48

Bagging vs Boosting #datascience #machinelearning #bagging #boosting #ensemble #statistics
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11K views
4:03

How to Fine-tune Large Language Models Like ChatGPT with Low-Rank Adaptation (LoRA)
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2.3K views
7:08

Multivariate Normal (Gaussian) Distribution Explained
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29K views
0:58

P-Values Explained #datascience #machinelearning #statistics #maths #math #mathematics
DataMListic
457 views
1:00

Why we build deep neural networks #machinelearning #deeplearning #neuralnetworks #datascience
DataMListic
781 views
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