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Complete Machine Learning,NLP Bootcamp MLOPS & Deployment - Panter - 14.07.2024
![[Bild: 603d45ef557c6edef4d4e27d1c487098.jpg]](https://i123.fastpic.org/big/2024/0709/98/603d45ef557c6edef4d4e27d1c487098.jpg)
Complete Machine Learning,NLP Bootcamp MLOPS & Deployment
Published 6/2024
Created by Krish Naik
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 218 Lectures ( 47h 25m ) | Size: 50.2 GB
Master the theory, practice, and math behind ML,NLP. Build real-world projects with MLOPS, git, Dockers with deployment
[b]What you'll learn:[/b]
Master foundational and advanced Machine Learning and NLP concepts.
Apply theoretical and practical knowledge to real-world projects using Machine learning,NLP And MLOPS
Understand and implement mathematical principles behind ML algorithms.
Develop and optimize ML models using industry-standard tools and techniques.
Understand The Core intuition of Deep Learning such as optimizers,loss functions,neural networks and cnn
Requirements:
Basic understanding of high school mathematics (algebra and statistics).
Familiarity with programming concepts (Python preferred).
Willingness to learn and apply theoretical and practical knowledge.
Access to a computer with internet connectivity for hands-on practice.
Description:
Are you looking to master Machine Learning (ML) and Natural Language Processing (NLP) from the ground up? This comprehensive course is designed to take you on a journey from understanding the basics to mastering advanced concepts, all while providing practical insights and hands-on experience.What You'll Learn:Foundational Concepts: Start with the basics of ML and NLP, including algorithms, models, and techniques used in these fields. Understand the core principles that drive machine learning and natural language processing.Advanced Topics: Dive deeper into advanced topics such as deep learning, reinforcement learning, and transformer models. Learn how to apply these concepts to build more complex and powerful models.Practical Applications: Gain practical experience by working on real-world projects and case studies. Apply your knowledge to solve problems in various domains, including healthcare, finance, and e-commerce.Mathematical Foundations: Develop a strong mathematical foundation by learning the math behind ML and NLP algorithms. Understand concepts such as linear algebra, calculus, and probability theory.Industry-standard Tools: Familiarize yourself with industry-standard tools and libraries used in ML and NLP, including TensorFlow, PyTorch, and scikit-learn. Learn how to use these tools to build and deploy models.Optimization Techniques: Learn how to optimize ML and NLP models for better performance and efficiency. Understand techniques such as hyperparameter tuning, model selection, and model evaluation.Who Is This Course For:This course is suitable for anyone interested in learning machine learning and natural language processing, from beginners to advanced learners. Whether you're a student, a professional looking to upskill, or someone looking to switch careers, this course will provide you with the knowledge and skills you need to succeed in the field of ML and NLP.Why Take This Course:By the end of this course, you'll have a comprehensive understanding of machine learning and natural language processing, from the basics to advanced concepts. You'll be able to apply your knowledge to build real-world projects, and you'll have the skills needed to pursue a career in ML and NLP.Join us on this journey to master Machine Learning and Natural Language Processing. Enroll now and start building your future in AI.
Who this course is for:
Aspiring data scientists and machine learning enthusiasts.
Students and professionals looking to enhance their ML and NLP skills.
Beginners with a basic understanding of programming and mathematics.
Anyone interested in understanding and applying machine learning and NLP techniques from scratch to advanced levels.
Beginners Python Developer who wants to get into the Data Science field
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