Скачать или смотреть Machine Learning | 10 | Models for sequential Data (Markov Models, Word2Vec and LSTMs)

Machine Learning | 10 | Models for sequential Data (Markov Models, Word2Vec and LSTMs)

errata: In slide 20, one of the factors of the decomposed joint probability is missing.

In the last lectures, we will discuss various deviations from the standard offline machine learning recipe we've discussed so far. Today: learning sequences. Language, music, time series and so on.
In the first half, we discuss the simple, but powerful approach of the Markov Model, and our first embedding model: word2vec.

In the second half, we discuss recurrent neural networks. A very powerful, but a bit more complex approach to dealing with sequences. Specifically, we focus on the LSTM; one of the most popular neural networks in use today.

By Vrije Universiteit Amsterdam
Slides: https://bit.ly/3wxnP71
Course Materials: https://bit.ly/39GeXlt

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What are Markov models used for?

How does Markov model work?

What is Markov switching model?

What is Markov theory?

What is a first order Markov model?

What is the difference between Markov model and hidden Markov model?

Why is model selection used in hmm?

Where does the hidden Markov model is used?

What is the difference between Markov chain and Markov process?

What is meant by stochastic process?

What do you mean by Markov chains give any 2 examples?

What is a regular Markov chain?
What is Word2Vec used for?
What are LSTMs used for?

Why is Lstm better than RNN?

What is Lstm and how it works?

Is CNN better than Lstm?

Which is better Lstm or GRU?

Is RNN deep learning?

Is Lstm an algorithm?

What is the hidden state in Lstm?

What are some common problems with Lstm?

Is Gru faster than Lstm?

Is Lstm a RNN?

How long does it take to train Lstm?

How many layers does Lstm have?

Why Tanh is used in Lstm?

Why is Tanh used in RNN?

Why is RELU not used in RNN?

What is the range of Tanh?

What activation function does Lstm use?



Is Word2Vec machine learning?



What is Word2Vec explain with example?

What is Word2Vec embedding?

How does Gensim Word2Vec work?

Is Word2Vec supervised or unsupervised?

What does embedding mean?

How do I use Word embeds for text classification?

How do bag words work?

What are Embeddings in machine learning?

How are Embeddings trained?



How do I calculate embeds in Word?

What is a Word2Vec model?

What is CBOW model?

What is Doc2Vec model?

What is the continuous bag of words CBOW approach?

How do you plot a word embed?

What is the difference between GloVe and Word2Vec?

What is word embedding in NLP?

Is Bert a word embedding?

Why do we need to embed words?

Why is self supervised learning?


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