UTKARSH's starred repositories
Python-Practice-Solved-Programs
This Repository is a collection of all of my solved problems on Hacker rank in Python course. This repository contain basic program from hello world to some advanced program like puzzle or Game
Hackerrank_Python_Solutions
HackerRank Python solutions and challenges.
Python-Hackerrank-Solutions
Hackerrank Solutions for Python - Total 115 Challenges
sentiment-analysis-with-LLM
The project demonstrates an example of how to use a supervised learning task using GPT-3.5 with JSON export, evaluating reviews in Italian Language.
scikit-learn-interview-questions
🟣 Scikit-Learn interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
nlp-interview-questions
🟣 NLP interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
data-processing-interview-questions
🟣 Data Processing interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
model-evaluation-interview-questions
🟣 Model Evaluation interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
sql-ml-interview-questions
🟣 SQL interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
statistics-interview-questions
🟣 Statistics interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
python-ml-interview-questions
🟣 Python ML interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
llms-interview-questions
🟣 LLMs interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
data-scientist-interview-questions
🟣 Data Scientist interview questions and answers to help you prepare for your next machine learning and data science interview in 2024.
Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
Casting-Defect-Detection-and-Classification-Model-using-CNN
A Machine learning model to detect defects in industrial pump impeller casts and classify the type of it.
trading-bot
Stock Trading Bot using Deep Q-Learning
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
vertex-ai-samples
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
awesome-generative-ai-guide
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
Generative_AI_LLMs
Generative AI with Large Language Models on Coursera offered by Deeplearning.AI and AWS.
recruitment_challenge
recruitment challenge for job at HAMS
customer-support-llm-chatbot-training-dataset
A dataset for training customer service chatbot models on LLMs
E-Commerce-Chatbot
Chatbot for E-Commerce Related Questions
A-Simple-Chatbot-
A chatbot (also known as a talkbot, chatterbot, Bot, IM bot, interactive agent, or Artificial Conversational Entity)The classic historic early chatbots are ELIZA (1966) and PARRY (1972).More recent notable programs include A.L.I.C.E., Jabberwacky and D.U.D.E (Agence Nationale de la Recherche and CNRS 2006). While ELIZA and PARRY were used exclusively to simulate typed conversation, many chatbots now include functional features such as games and web searching abilities. In 1984, a book called The Policeman's Beard is Half Constructed was published, allegedly written by the chatbot Racter (though the program as released would not have been capable of doing so). One pertinent field of AI research is natural language processing. Usually, weak AI fields employ specialized software or programming languages created specifically for the narrow function required. For example, A.L.I.C.E. uses a markup language called AIML, which is specific to its function as a conversational agent, and has since been adopted by various other developers of, so called, Alicebots. Nevertheless, A.L.I.C.E. is still purely based on pattern matching techniques without any reasoning capabilities, the same technique ELIZA was using back in 1966. This is not strong AI, which would require sapience and logical reasoning abilities. Jabberwacky learns new responses and context based on real-time user interactions, rather than being driven from a static database. Some more recent chatbots also combine real-time learning with evolutionary algorithms that optimise their ability to communicate based on each conversation held. Still, there is currently no general purpose conversational artificial intelligence, and some software developers focus on the practical aspect, information retrieval. Chatbot competitions focus on the Turing test or more specific goals. Two such annual contests are the Loebner Prize and The Chatterbox Challenge (offline since 2015, materials can still be found from web archives). According to Forrester (2015), AI will replace 16 percent of American jobs by the end of the decade.Chatbots have been used in applications such as customer service, sales and product education. However, a study conducted by Narrative Science in 2015 found that 80 percent of their respondents believe AI improves worker performance and creates jobs.[citation needed] is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatterbots use sophisticated natural language processing systems, but many simpler systems scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database. The term "ChatterBot" was originally coined by Michael Mauldin (creator of the first Verbot, Julia) in 1994 to describe these conversational programs.Today, most chatbots are either accessed via virtual assistants such as Google Assistant and Amazon Alexa, via messaging apps such as Facebook Messenger or WeChat, or via individual organizations' apps and websites. Chatbots can be classified into usage categories such as conversational commerce (e-commerce via chat), analytics, communication, customer support, design, developer tools, education, entertainment, finance, food, games, health, HR, marketing, news, personal, productivity, shopping, social, sports, travel and utilities. Background