Name: Sachin Lokesh
Type: User
Company: Amazon and Plaksha TLF
Bio: Applied Science and Product Management
Interested in building products that improves people's life/work at scale.
Location: Bangalore, India
Blog: https://github.com/Sachinhl021x/sachinlokesh.github.io
Sachin Lokesh's Projects
Conversational AI with RASA, published by Packt
My Learnings of ConversationalAI using Rasa Framework
A mechanical design model to approximate mass and factor-of-safety of various engine components
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Myself along with another member had conducted Python labs for 90+ students teaching them fundamentals to advance python
The intent classification task aims to tag utterance or sen- tences with a predefined label. Intent classification models can be either rule-based and deep learning-based. The rule based methods aim to classify the intents using pre-defined rules and requires deep domain knowledge where as deep learning-based models aim to classifies the intents by learning the inherent pat- terns between text and their labels. Minaee et al. Classical machine learning models require handcrafted features to be fed into a classifier for intent prediction. With the advancement in the word embedding [33] and neural network architectures, neural based intent classification models are able to map the text vector into a low-dimensional feature vector and extract the key features to predict the intent. We approach the intent classification task using supervised deep learning models
Transformers for Natural Language Processing, published by Packt