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Machine Learning with TensorFlow

Build and deploy machine learning models using TensorFlow and Keras. Cover neural networks, CNNs, RNNs, transfer learning, and production deployment.

4.0 (1 ratings) • 0 students
  1. ▶️ Recorded Course
  2. Course Instructor: Fun Plus
  3. Category: Data Science
  4. Sub Category: Machine Learning
  5. Child Category: N/A
  6. Last updated: 01/2026
  7. Language: English

Machine Learning with TensorFlow

Data Science > Machine Learning > N/A

Build and deploy machine learning models using TensorFlow and Keras. Cover neural networks, CNNs, RNNs, transfer learning, and production deployment.

Course Requirements

Solid understanding of Python programming

Basic knowledge of linear algebra and calculus is helpful

A computer with a modern GPU is recommended but not required (Google Colab can be used)

Course Details

Dive deep into machine learning and deep learning with TensorFlow, the most widely used ML framework in the industry. This course takes you from understanding basic ML concepts to building and deploying sophisticated neural network models.

You will learn linear regression, classification, clustering, convolutional neural networks for image recognition, recurrent neural networks for sequence data, natural language processing, generative adversarial networks, and reinforcement learning fundamentals. Each topic includes theoretical explanations followed by hands-on TensorFlow implementations.

The course culminates with a capstone project where you build, train, and deploy a production-ready ML model using TensorFlow Serving and Docker. You will graduate with the skills to tackle real-world machine learning challenges.