TensorGo Technologies Interview Questions and Answers

An application-based round in my case involves a chatbot that is based on LLM (Language Model).

Q1. Can you describe the projects you have worked on?
Ans. 
I have worked on various projects including developing a mobile app for tracking fitness goals and creating a website for a local non-profit organization.
• Developed a mobile app for tracking fitness goals using React Native and Firebase

• Created a website for a local non-profit organization using HTML, CSS, and JavaScript

• Collaborated with a team to implement new features and fix bugs in existing projects
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Q2. How does a large language model (LLM) work?
Ans. 
A large language model (LLM) uses deep learning techniques to understand and generate human language.
• LLMs are trained on vast amounts of text data to learn patterns and relationships in language.

• They use neural networks to process and generate text, allowing them to understand and produce human-like language.

• Examples of LLMs include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representa...read more
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It was on python and sql mostly

Data science, sql and deep learning

Speech to Speech bot

Q1. Write code to implement CNN on notepad
Ans. 
Implementing CNN code on notepad
• Start by defining the CNN architecture with layers like Conv2D, MaxPooling2D, Flatten, and Dense

• Compile the model with appropriate loss function and optimizer

• Train the model on a dataset using fit() function

• Evaluate the model's performance using test data and metrics like accuracy
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Q2. Explain the internal mechanism of LLM ?
Ans. 
LLM stands for Latent Language Model, which is a type of machine learning model used for natural language processing tasks.
• LLM is a type of language model that learns to predict the next word in a sentence based on the context provided.

• It uses latent variables to capture the underlying structure of the language.

• LLM can be trained using unsupervised learning techniques such as autoencoders or variational autoencoders.

• Ex...read more
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Q1. Work flow of you project
Ans. 
The project workflow involves planning, development, testing, deployment, and maintenance to ensure a successful software delivery.
• Planning: Define project scope, requirements, and timelines. Example: Creating a project roadmap with milestones.

• Development: Write code using chosen technologies. Example: Using React for frontend and Node.js for backend development.

• Testing: Conduct unit, integration, and user acceptance t...read more
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Q1. This is not done yet
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