Все публикации

0:07:42

2.2 Imputation Strategies for missing values

0:16:10

2.1 Exploratory Data Analysis EDA

0:10:27

1.3 Splitting, Applying, and Combining Data Sources

0:22:44

1.2 Implementing Pandas Functions for Machine Leaning Models

0:24:16

1.1 Loading and Summarizing the Titanic Dataset

0:06:36

Python Programming Development Environment Setup

0:12:53

PYTHON PACKAGES AND MODULES for Machine Learning and Deep Learning

0:23:11

Introduction to AI, ML and Deep learning

0:11:33

Load and Manipulate Images with Keras API of TensorFlow

0:19:15

Feature Extraction from Text Data in NLP (General and Specific Features)

0:19:16

Introduction to Computer Vision and Deep Learning with Tensoeflow, Pytorch and OpenCV

0:06:54

Language Translation in Natural Language Processing

0:06:48

Lemmatization, Singularizing and Pluralizing Words in NLP

0:10:25

Stemming with RegexpStemmer and Porter Stemmer Algorithms

0:14:46

Text Cleaning with Regular Expressions, NLTK and textblob Libraries in NLP

0:05:28

Feature Extraction Introduction in NLP

0:05:16

Preprocessing of Raw Text in NLP

0:03:21

Sentence boundary detection

0:05:12

Word Sense Disambiguation

0:05:55

Named Entity Recognition (NER) in Natural Language Processing

0:04:06

Lemmatization in Natural Language Proessing

0:05:35

Stemming in the Natural Language Processing

0:04:49

Spelling Correction in NLP

0:04:40

Text Normlization in Natural Language Processing