Word embeddings like Word2Vec and GloVe have revolutionized natural language processing, offering compact and dense representations of word meanings. However, these embeddings typically represent words as real-valued vectors, potentially limiting their ability to capture complex semantic relationships. In this proposal, we explore an alternative approach:...

Hi, does anyone know of a French L2 GEC dataset (that was published at a conference)? submitted by /u/R-e-v-e-r-i-e- [link] [comments]

My primary expertise is audio processing, but i believe this task happens in other domains too: running a model on chunks of infinitely long input. while for some architectures it is straightforward, it can get tedious for convolutional nets. I put together a comprehensive tutorial how to build a streaming ML applications: https://balacoon.com/blog/streaming_inference/....

I'm planning to dive into ML and I'd like to specialize in a special field. What are the promising subfields of ML and which ones are high demand? submitted by /u/Dramatic_Chance9577 [link] [comments]

​ https://preview.redd.it/jpiyt4b9yhwc1.png?width=1165&format=png&auto=webp&s=95d80f8f9c9241d722717ad25215be4077d541ca Based on the MSE looks good right? But why is my R^2 starting off so negative and approaching 0? Could it be a bug in how i am calculating it? This happened after i min maxed the labels before training. This is an LSTM...

Hi we have our custom domain data in tables which can be exported to csv. I need to train the model to understand this data and answer questions like whats in table1 thats not in table2 or custom questions specific to domain and data. Is there a framework or libraries available that can do this already? submitted by /u/EquivalentPass3851 [link]...