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Normalized Nerd @UC7Fs-Fdpe0I8GYg3lboEuXw@youtube.com

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05:48
Standardization vs Normalization Clearly Explained!
09:51
GridSearchCV | Hyperparameter Tuning | Machine Learning with Scikit-Learn Python
20:08
Multiprocessing in Python | Basics to Advanced | Tutorial - 1
07:47
Covariance Clearly Explained!
08:01
Random Forest Algorithm Clearly Explained!
09:03
What's my Data Science background? QnA | NORMALIZED NERD
18:27
Markov Chains: Simulation in Python | Stationary Distribution Computation | Part - 7
11:01
Forward Algorithm Clearly Explained | Hidden Markov Model | Part - 6
17:15
Naive Bayes Classifier in Python (from scratch!)
14:03
Decision Tree Regression in Python (from scratch!)
09:17
Decision Tree Regression Clearly Explained!
17:43
Decision Tree Classification in Python (from scratch!)
10:33
Decision Tree Classification Clearly Explained!
11:58
Watch this to learn Machine Learning in 2021!
09:32
Hidden Markov Model Clearly Explained! Part - 5
13:28
Markov Chains: Generating Sherlock Holmes Stories | Part - 4
08:34
Markov Chains: n-step Transition Matrix | Part - 3
06:29
Markov Chains: Recurrence, Irreducibility, Classes | Part - 2
09:24
Markov Chains Clearly Explained! Part - 1
08:21
Monte Carlo Simulation with Card Games
06:27
Gambler's Fallacy vs Regression toward the Mean
06:42
The Central Limit Theorem Clearly Explained!
04:41
MegaFavNumbers - 115,132,219,018,763,992,565,095,597,973,971,522,401 is the last of its kind!
05:15
What is Norm in Machine Learning?
08:13
Why do we need Cross Entropy Loss? (Visualized)
11:53
The Math Behind Bayesian Classifiers Clearly Explained!
14:30
Top 11 Pandas Tricks Every Data Science Lover Should Know
17:29
GAN Generates English & Bengali Alphabets | How to Train a GAN?
17:04
The Math Behind Generative Adversarial Networks Clearly Explained!
10:11
A.I. Evolves to Play Hit the Ball | Neural Network + Genetic Algorithm
14:59
Text Summarization & Keyword Extraction | Introduction to NLP
24:19
Autoencoders Made Easy! (with Convolutional Autoencoder)
20:46
DBSCAN Algorithm | Machine Learning with Scikit-Learn Python
17:08
Sarcasm is Very Easy to Detect! GloVe + LSTM
06:57
The Course Loop and How to Break It
27:42
K-means Clustering in Python
22:32
KNN Classification & Regression in Python
14:05
A.I. learns to play | Neural Network + Genetic Algorithm
50:25
A.I. beats the Game (full video)
13:48
Introduction to NLP | How to Train Custom Word Vectors
03:43
What is Recurrent Neural Network?
21:12
Introduction to NLP | GloVe & Word2Vec Transfer Learning
14:05
Synthetic Data: Future of Data Science and AI
23:10
Linear Regression: OLS, Ridge, Lasso and beyond
23:15
Introduction to NLP | GloVe Model Explained
23:10
Introduction to NLP | Word Embeddings & Word2Vec Model
14:02
Introduction to NLP | Text Cleaning and Preprocessing
10:56
Introduction to NLP | TF-IDF
22:24
Introduction to NLP | Bag of Words Model
13:41
Machine Learning with Scikit-Learn Python | RMSE, MAE, RMSLE, adj R2 and more
14:59
R squared and Adjusted R squared Explained
10:50
Machine Learning with Scikit-Learn Python | ROC & AUC
20:46
ROC and AUC Explained | Concept & Example
20:49
Neural Network to Detect Chat Screenshots
26:31
P vs NP | What are NP-Complete and NP-Hard Problems?
16:38
Maximum Likelihood Estimate in Machine Learning
11:08
Machine Learning with Scikit-Learn Python | Logistic Regression
23:40
Data Visualization in Python | How to Interpret?
24:48
Transfer Learning | How to Extract Features from Images?
20:22
Feature Selection | Top 10 Ways to Find the Best Features
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