Complete Chatbot Using Machine Learning Project
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English
| Duration: 1h 0m
Learn CHATBOT Using Machine Learning Project From Scratch
What you'll learn
Complete CHATBOT Using Machine Learning Project
Clean and tokenize the text data to prepare it for training.
Extract relevant features from the text data, such as word embeddings and contextual information.
Implement neural network models using popular deep learning frameworks like TensorFlow or PyTorch.
Requirements
Basic knowledge of Python programming and machine learning concepts.
Description
Course Title: Complete Chatbot Using Machine Learning Project with Neural NetworkCourse Description:Welcome to the "Complete Chatbot Using Machine Learning Project with Neural Network" course! In this comprehensive project-based course, you'll learn how to build a chatbot using machine learning techniques, with a focus on neural network models. Chatbots are intelligent conversational agents capable of understanding and responding to human queries, and they find applications in customer service, virtual assistants, and more.What You Will Learn:Introduction to Chatbots:Understand the concept and importance of chatbots in modern applications..Data Collection and Preprocessing:Collect and preprocess conversational data from various sources, such as chat logs and customer support transcripts.Clean and tokenize the text data to prepare it for training.Feature Engineering:Extract relevant features from the text data, such as word embeddings and contextual information.Understand the importance of feature representation in building effective chatbots.Building Neural Network Models:Learn about neural network architectures suitable for chatbot applications, such as sequence-to-sequence models and transformers.Implement neural network models using popular deep learning frameworks like TensorFlow or PyTorch.Model Training and Evaluation:Split the dataset into training, validation, and testing sets, and train the neural network models.Evaluate the performance of the chatbot models using metrics such as accuracy, perplexity, and response coherence.Fine-Tuning and Optimization:Fine-tune the neural network models by adjusting hyperparameters and experimenting with different architectures.Explore techniques for optimizing chatbot performance, such as beam search and attention mechanisms.Integration and Deployment:Integrate the trained chatbot models into a user-friendly interface, such as a web application or messaging platform.Deploy the chatbot to a cloud platform or server for real-world usage.User Experience and Interaction Design
esign intuitive user interfaces and conversational flows for interacting with the chatbot.Implement features such as natural language understanding (NLU) and context awareness to enhance user experience.Why Enrollractical Project Experience: Gain hands-on experience by building a fully functional chatbot project from scratch.Cutting-Edge Skills: Develop skills in natural language processing, deep learning, and conversational AI.Real-World Applications: Learn how to apply machine learning techniques to solve real-world problems and improve user experiences.Enroll now and embark on your journey to building intelligent chatbots with machine learning and neural networks! Overview
Section 1: Introduction To Complete CHATBOT Using Machine Learning Project
Lecture 1 Introduction To Course
Lecture 2 Introduction To Machine Learning
Section 2: Complete CHATBOT Using Machine Learning Project
Lecture 3 CHATBOT CLASS 1 : IMPORT PACKAGES
Lecture 4 CHATBOT CLASS 2 : IMPORT DATASET
Lecture 5 CHATBOT CLASS 3 : LABLE ENCODER
Section 3: Complete CHATBOT Using Machine Learning Project
Lecture 6 CHATBOT CLASS 4 : TOKENIZATION OF DATASET
Lecture 7 CHATBOT CLASS 5 : TRAINING NEURAL NETWORK
Lecture 8 CHATBOT CLASS 6 : SAVE TRAINED MODEL
Lecture 9 CHATBOT CLASS 7 : OUTPUT AND CONCLUSION
Developers looking to build intelligent chatbots for various applications, including customer service and virtual assistants.,Data enthusiasts interested in natural language processing (NLP) and conversational AI.
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