educative.io

Natural Language Processing with Machine Learning (Adaptilab)


Word Embeddings - Embeddings Learn the basics of word embeddings and why they're used. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4836603769913344). Word Embeddings - Embedding Loss Learn about different loss functions for embedding training. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6258192713515008). Word Embeddings - Cosine Similarity Implement normalized cosine similarity to evaluate the embedding model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6248937998516224). Language Model - Introduction Have questions about Introduction? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6224155366129664). Language Model - Language Model Learn how language models are trained to calculate word probabilities. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6030340151836672). Language Model - Dropout Use dropout to help train a better LSTM model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4903170662727680). Language Model - LSTM Output Run an LSTM model on input sequences and retrieve the output. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5657756956622848). Language Model - Calculating Loss Calculate the loss for your LSTM model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6309436236759040). Language Model - Predictions Create word predictions based on the output of your LSTM model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4837219107864576). Language Model - Tensor Indexing Use tensor indexing to retrieve the model's final word prediction. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6210864187179008). Language Model - Quiz Have questions about Quiz? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6337872628023296). Text Classification - Introduction Have questions about Introduction? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5098447608741888). Text Classification - Sentiment Analysis Learn about sentiment analysis and how it relates to NLP. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4922629683150848). Text Classification - Bidirectional LSTM Create and run a bidirectional LSTM model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6029070569570304). Text Classification - Logits Calculate logits based on the final output of the model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6272371876954112). Seq2Seq Model - Introduction Have questions about Introduction? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5466120616148992). Text Classification - Classification Use the model to classify a given text sequence. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6224347515584512). Text Classification - Improving the Model Tips and advice on how to improve the BiLSTM model performance. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6230724115955712). Text Classification - Quiz Have questions about Quiz? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6289233918558208). Seq2Seq Model - Training Data Understand how training data is processed for sequence to sequence models. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5962503676755968). Seq2Seq Model - Final States Learn about the final state output of an LSTM and BiLSTM. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4864996993400832). Seq2Seq Model - Encoder-Decoder Learn about the encoder-decoder model architecture. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5467390198415360). Seq2Seq Model - Attention Learn about the attention mechanism and why it's important. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6036598992928768). Seq2Seq Model - Training Helper Create a Training Helper object for training the decoder. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5093418806018048). Seq2Seq Model - Decoder Object Learn about the decoder object for the encoder-decoder model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4824619200544768). Seq2Seq Model - Decoding Output Decode the model's outputs for training and inference. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5179562629529600). Seq2Seq Model - Calculating Loss Calculate the model's loss based on logits and sparse outputs. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5466620795289600). Seq2Seq Model - Inference Decoding Understand the difference between training and inference decoding. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5845030566625280). Seq2Seq Model - Model Improvement Learn strategies for improving an encoder-decoder model. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5116321786232832). Seq2Seq Model - Datasets An overview of some useful datasets to train a seq2seq model with. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5072850459295744). Seq2Seq Model - Course Conclusion Have questions about Course Conclusion? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5921809696292864). Seq2Seq Model - Quiz Have questions about Quiz? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6168717136232448). Text Classification - Embeddings Use TensorFlow's built-in functions for creating embeddings. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5094807003201536). Text Classification - Loss Calculate the model's sigmoid cross entropy loss. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4902061353205760). Seq2Seq Model - Combined State Combine the final states for a BiLSTM into usable initial states. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5399553723334656). Word Embeddings - Embedding Matrix Create a trainable embedding matrix to calculate word embeddings. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4831494520438784). What you'll learn from this course - Overview Have questions about Overview? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5822148604067840). Language Model - RNN/LSTM Learn about recurrent neural networks and LSTM cells. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5742512582950912). Word Embeddings - Vocabulary Become accustomed to the meaning of "vocabulary" for NLP tasks. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4531857049780224). Word Embeddings - Skip-gram Understand the difference between skip-gram and CBOW embedding models. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5071831427973120). Word Embeddings - K-Nearest Neighbors In this chapter, we will be learning how to calculate K-nearest neighbors based on cosine similarity. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/6197731334815744). Word Embeddings - Candidate Sampling Understand why candidate sampling is used for embedding training. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5924239007809536). Language Model - Padding Understand the purpose of padding with respect to tokenized sequences. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5118812380725248). Language Model - Multiple Layers Stack multiple LSTM cell layers for added performance. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5084964280336384). Word Embeddings - Introduction An overview of natural language processing and word embeddings. View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/5076480646184960). Word Embeddings - Quiz Have questions about Quiz? Go for it! View the lesson [here](https://www.educative.io/collection/page/6083138522447872/5255772847996928/4903971758014464).
About the Natural Language Processing with Machine Learning (Adaptilab) category [Natural Language Processing with Machine Learning (Adaptilab)] (1)