Machine Learning Title - Master the Machine Muse: Build Generative AI with ML
Machine Learning Title - Master the Machine Muse: Build Generative AI with ML
Lectures -41
Duration -6.5 hours
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Course Description
Unlock the creative potential of artificial intelligence with "Master the Machine Muse: Build Generative AI with ML." This comprehensive course takes you on an exciting journey into the world of generative AI, blending the art of machine learning with the science of creativity. Whether you're an aspiring data scientist, a tech enthusiast, or a creative professional looking to harness the power of AI, this course will provide you with the skills and knowledge to build and deploy your generative models.
Course Highlights:
- Introduction to Generative AI: Understand the fundamentals of generative AI and its applications across various domains such as art, music, text, and design.
- Foundations of Machine Learning: Learn the core concepts of machine learning, including supervised and unsupervised learning, and how they apply to generative models.
- Deep Learning for Creativity: Dive deep into neural networks and explore architectures like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformers that are driving the generative AI revolution.
- Hands-On Projects: Engage in practical, hands-on projects that will guide you through the process of building your generative models. From generating art to composing music, you'll experience the thrill of creating with AI.
- Python Programming: Gain proficiency in Python programming, focusing on libraries and frameworks essential for generative AI, such as TensorFlow, PyTorch, and Keras.
- Ethics and Future of Generative AI: Discuss the ethical considerations and future implications of generative AI, ensuring you are well-equipped to navigate this rapidly evolving field responsibly.
Who Should Enroll:
- Data Scientists and Machine Learning Engineers looking to specialize in generative models.
- Artists, Musicians, and Designers interested in exploring AI as a tool for creativity.
- Tech Enthusiasts and Innovators eager to stay ahead in the field of AI.
- Students and Professionals aiming to enhance their skill set with cutting-edge technology.
Goals
By the end of this course, you will:
- Have a strong grasp of generative AI concepts and techniques.
- Be able to build and train generative models using state-of-the-art machine learning frameworks.
- Understand the ethical considerations and potential impacts of generative AI.
- Be prepared to apply generative AI skills in real-world projects and innovative applications.
Join us in "Master the Machine Muse: Build Generative AI with ML" and embark on a creative journey that merges technology with imagination, empowering you to shape the future of AI-driven creativity.
Prerequisites
- Basic understanding of Python programming.
- Familiarity with machine learning concepts is beneficial but not required.
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Curriculum
Check out the detailed breakdown of what’s inside the course
Logistic Regression Fundamentals
3 Lectures
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Logistic Regression: From Zero to Hero 11:00 11:00
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Demystifying Logistic Regression Math 09:37 09:37
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Logistic Regression: Real-World Examples You Can't Ignore 10:18 10:18
Data Preparation and Evaluation
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Logistic Regression for NLP
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Logistic Regression in Action: COVID-19 Case Study
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Text Preprocessing and EDA
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Feature Engineering for NLP
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Regularization and Model Comparison
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Linear Regression and Decision Trees
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Decision Tree Algorithms
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Decision Trees with Categorical Data
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Visualization and Analysis
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Advanced Data Analysis
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Clustering Techniques
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Advanced Clustering and Evaluation
2 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
AKHIL VYDYULA
Hello, I'm Akhil, an Associate Consultant at Atos India with a focus on the Advisory Consulting practice, specializing in Data and Analytics. My professional journey has led me through various facets of data analysis and modeling, particularly in the BFSI sector, where I've had the privilege of overseeing the full lifecycle of development and execution.
My skill set encompasses a wide range of data-related tasks, including data wrangling, feature engineering, algorithm development, model training, and implementation. I thrive on leveraging data mining techniques such as statistical analysis, hypothesis testing, regression analysis, as well as both unsupervised and supervised machine learning processes to extract meaningful insights and drive data-informed decisions. I'm particularly passionate about risk identification through decision models, and I've honed my expertise in Machine Learning Algorithms, Data/Text Mining techniques, and Data Visualization to effectively address these challenges.
Currently, I'm immersed in an exciting Amazon cloud project that involves end-to-end development of ETL processing. In this role, I craft ETL processing code using PySpark/Spark SQL to extract data from S3 buckets, perform necessary transformations, execute scripts using EMR services, and load consolidated data into Postgres SQL (RDS/Redshift) on a full, incremental, and live basis. To streamline this process, I've automated it by creating jobs in Step functions, which trigger EMR instances to run scripts in a specific order and send notifications upon execution status changes. The scheduling of these Step functions is achieved through event bridge rules.
Additionally, I've worked extensively with AWS Glue, using it to replicate source data from on-premises systems to raw-layer S3 buckets via AWS DMS services. One of my key strengths lies in my ability to understand the nuances of data and apply the right transformations to convert data from multiple tables into key-value pairs. Furthermore, I've optimized the performance of stored procedures in Postgres SQL to execute second-level transformations by efficiently joining multiple tables and loading the data into final tables.
I'm passionate about harnessing the power of data to drive actionable insights and improve business outcomes. If you share this passion or are interested in collaborating on data-driven projects, feel free to connect with me. Let's explore the endless possibilities that data analytics has to offer!
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