Description for Python and Pandas for Data Engineering
Techniques for Word Feature Conversion: Gain knowledge of methodologies such as one-hot encoding, bag-of-words, embeddings, and embedding bags for the transformation of words into features.
Contextual Embedding Utilizing Word2Vec: Acquire practical expertise in the application of Word2Vec models for the generation of contextual embeddings.
Constructing a Fundamental Neural Network Language Model: Comprehend the methodology for constructing a fundamental language model utilizing a neural network.
Applying N-Gram and Sequence-to-Sequence Models: Investigate N-gram models and sequence-to-sequence architectures for applications including document classification, text analysis, and sequence transformation.
Level: Beginner
Certification Degree: yes
Languages the Course is Available: 1
Offered by: On edX provided by AI
Duration: 3�6 hours per week 4 weeks (approximately)
Schedule: Flexible
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