LTIMindtree Senior Software Engineer 1 Interview Questions and Answers

I utilized a modern tech stack including React, Node.js, and MongoDB for building scalable web applications.

• React for front-end development: Enables building dynamic user interfaces with reusable components.

• Node.js for back-end: Allows for handling multiple requests efficiently with non-blocking I/O.

• MongoDB as a database: Provides flexibility with a schema-less structure, ideal for handling diverse data types.

• Express.j...read more

RAG architecture combines retrieval and generation for enhanced information processing in AI applications.

• RAG stands for Retrieval-Augmented Generation, integrating retrieval mechanisms with generative models.

• It allows models to access external knowledge bases, improving the accuracy of generated responses.

• For example, a chatbot using RAG can pull relevant information from a database to answer user queries more effecti...read more

LangChain is a framework for developing applications powered by language models.

• Facilitates integration of LLMs (Large Language Models) into applications.

• Supports various use cases like chatbots, summarization, and question answering.

• Provides tools for managing prompts and chaining together multiple LLM calls.

• Example: Building a chatbot that can answer questions based on a specific dataset.

• Includes components for memor...read more

Fine-tuning models involves adjusting pre-trained models on specific datasets to improve performance for targeted tasks.

• Transfer Learning: Use a pre-trained model (e.g., BERT) and fine-tune it on a smaller dataset for a specific task.

• Layer Freezing: Freeze certain layers of a model to retain learned features while training only the last few layers.

• Learning Rate Adjustment: Use a lower learning rate for fine-tuning to a...read more

Fine-tuning models enhances their performance on specific tasks by adapting pre-trained models to new data and requirements.

• Improves accuracy: Fine-tuning allows models to learn from domain-specific data, enhancing their predictive capabilities.

• Saves time: Instead of training a model from scratch, fine-tuning leverages existing knowledge, reducing training time significantly.

• Customizes performance: Tailors the model to...read more

LSTM RNNs are advanced neural networks designed to learn from sequences, effectively handling long-term dependencies in data.

• LSTM stands for Long Short-Term Memory, a type of recurrent neural network (RNN).

• LSTMs are designed to remember information for long periods, making them suitable for tasks like language modeling.

• They use special gates (input, output, forget) to control the flow of information.

• Example: LSTMs can ...read more

Chunking techniques involve breaking data into smaller, manageable pieces for easier processing and understanding.

• Improves memory retention by grouping information (e.g., phone numbers: 123-456-7890).

• Facilitates data processing in algorithms (e.g., processing large datasets in smaller batches).

• Enhances user experience in UI design by organizing content into sections (e.g., multi-step forms).

• Used in natural language pro...read more

Comparing LLMs involves evaluating performance, architecture, and use cases to determine the best fit for specific applications.

• GPT-3: Known for its versatility and ability to generate human-like text, making it suitable for creative writing and chatbots.

• BERT: Excels in understanding context and semantics, ideal for tasks like sentiment analysis and question answering.

• T5: A text-to-text transformer that can handle vari...read more

Pipes in Angular are used for transforming data in templates.

• Pipes are used to format data before displaying it in the view.

• Angular provides built-in pipes like date, currency, uppercase, lowercase, etc.

• Custom pipes can also be created for specific formatting needs.

• Pipes can be chained together for multiple transformations.

• Example: {{ birthday | date:'MM/dd/yyyy' }} will format the birthday date.

Lazy loading in Angular is a technique used to load modules only when they are needed, improving performance by reducing initial load time.

• Lazy loading helps in splitting the application into multiple bundles which are loaded on demand.

• It allows for faster initial loading times as only essential modules are loaded upfront.

• Lazy loading is achieved by using the loadChildren property in the route configuration of Angular.

• ...read more