TensorFlow: Data and Deployment Specialization
Utilize TensorFlow.js for browser-based model execution, TensorFlow Lite for mobile deployment, TensorFlow Data Services for optimized data management, and TensorFlow Hub, Serving, and TensorBoard for advanced deployment scenarios.
Description for TensorFlow: Data and Deployment Specialization
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by DeepLearning.AI
Duration: 1 month at 10 hours a week
Schedule: Flexible
Pricing for TensorFlow: Data and Deployment Specialization
Use Cases for TensorFlow: Data and Deployment Specialization
FAQs for TensorFlow: Data and Deployment Specialization
Reviews for TensorFlow: Data and Deployment Specialization
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for TensorFlow: Data and Deployment Specialization
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Replicate is a cloud platform simplifying machine learning model execution, offering a wide range of models, scalable API deployment, and usage-based billing to minimize costs.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Utilize Generative AI to optimize marketing creativity. Explore the potential of Generative AI to revolutionize and influence your marketing organization.
Learn the significance, use cases, history, and pros and cons of generative AI in a business context, with a focus on its relationship to machine learning and services at Amazon.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
Use AI skills to advance your engineering career. Acquire practical knowledge regarding deep learning methodologies for computer vision.
The "Introduction to Vertex AI" course provides a four-hour, practical, and fundamental overview of Vertex AI, ideal for professionals and enthusiasts aiming to leverage AI effectively.
Featured Tools
Preparing students for a future in artificial intelligence security, this course offers AI hacking, vulnerability discovery, and attack mitigating techniques.
Master coding basics and create a Hangman game using generative AI tools like Google Bard in a beginner-friendly, 1.5-hour guided project.
Real-World Applications of Machine Learning. Develop proficiency in the implementation of a machine learning undertaking.
Mastering Advanced Statistics for Data Science. Acquire the necessary knowledge and abilities to effectively communicate the choices and interpretations of models.
This course equips students with the necessary business leadership skills and technical knowledge to propel the success of ML.