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TensorFlow 2 QuickStart for beginners
Rating: 4.1 out of 5(70 ratings)
10,865 students

TensorFlow 2 QuickStart for beginners

Build, Train and Evaluate a Neural Network machine learning model that classifies images
Created byAcademy of Computing & Artificial Intelligence
Last updated 1/2024
English
English [Auto],

What you'll learn

  • Mastering TensorFlow 2 Fundamentals
  • Hands-On Neural Network
  • Optimizing Models for Performance
  • Demo & Source code

Explore related topics

Course content

1 section • 8 lectures • 39m total length

  • Introduction3:07

    Explore TensorFlow 2 quickstart for beginners, using Keras to build and train a neural network that classifies images, with hands-on data loading from a prebuilt dataset and evaluation.

  • Set up TensorFlow5:56

    Set up TensorFlow in Google Colab, import TensorFlow as tf, verify the version, upgrade to the latest package, load the dataset, scale pixels to 0-1, and prepare training/testing splits.

  • Load a dataset5:24

    Load the means dataset with tf.keras, split into training and test sets, and normalize pixel values to 0–1 to train a neural network that recognizes handwritten digits.

  • Build a machine learning model8:27

    Build a machine learning model with a tf.keras sequential architecture, using flatten 28 by 28 to 784 features, dense 128 with ReLU, dropout 0.2, and dense 10 for classification.

  • Define a loss function6:56

    Define a loss function using sparse categorical cross entropy for classification, with ground truth labels and logits, applying softmax internally to compute per-example loss.

  • Configure and compile the model4:45

    Configure and compile the model with Keras model.compile, using the Adam optimizer, a defined loss function, and accuracy as the metric. Understand how these choices steer training progress.

  • Train and evaluate your model4:30

    Train and evaluate a neural network with TensorFlow 2 using the Keras API, applying model.fit on X_train and Y_train for five epochs and evaluating on a test set.

  • Code - Demo0:01

Requirements

  • Basic python knowledge

Description

Course Title: "TensorFlow 2 Quickstart for Beginners: Your Gateway to Data Science and Machine Learning"

Are you ready to embark on an exciting journey into the world of data science and machine learning? Look no further! Our TensorFlow 2 Quickstart for Beginners course is your ultimate ticket to mastering the fundamentals of machine learning using the powerful TensorFlow framework.

Course Highlights:

  1. Hands-On Learning with TensorFlow 2: This course is not just about theory; it's a hands-on experience where you'll work directly with TensorFlow 2, the cutting-edge machine learning library.

  2. Effortless Setup with Google Colab: Say goodbye to complex installations! Our tutorial is hosted on Google Colab, allowing you to run Python programs directly in your browser. This seamless experience makes learning TensorFlow hassle-free.

  3. Build and Train Your Neural Network: From loading a prebuilt dataset to constructing a neural network model, this course guides you step-by-step. You'll master the art of building models that can classify images, a fundamental skill in the machine learning domain.

  4. Expert Guidance Using Keras: We leverage Keras, TensorFlow's high-level API, making the learning curve smooth for beginners. You'll load datasets, build models, and train neural networks with ease.

  5. Optimise Your Model with Dropout: Learn how to prevent overfitting and enhance your model's generalisation using the Dropout layer. Our course equips you with practical techniques to fine-tune your neural networks.

Why Invest in This Course?

  • Practical Skill Development: Gain hands-on experience and build a solid foundation in machine learning.

  • Highly Accessible Learning Environment: Our course is hosted on Google Colab, ensuring a hassle-free setup for everyone, regardless of your development environment.

  • Expertly Crafted Curriculum: Developed by TensorFlow Authors, this course follows industry best practices and standards.

  • Build Confidence in TensorFlow: Feel confident in your ability to set up TensorFlow, load datasets, and build and train your own machine-learning models.

Your Investment in Knowledge:

Enroll now and set yourself on a path to success in the dynamic field of data science and machine learning. Acquire practical skills, build confidence, and unlock the potential of TensorFlow 2. This course is not just an educational experience; it's an investment in your future success!

Join us, and let's explore the limitless possibilities of TensorFlow together. Click 'Enroll Now' and start your journey into the fascinating world of machine learning!


Who this course is for:

  • Beginners in Machine Learning

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