TensorFlow 101: Introduction to Deep Learning

BY
Udemy

Become familiar with the fundamental concepts and strategies involved in deep learning with Tensorflow.

Mode

Online

Fees

₹ 499 1499

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

Deep learning is a branch of artificial intelligence and machine learning that resembles how learners understand specific types of information. Data science, which also includes statistical data and predictive modeling, includes deep learning as a crucial aspect. TensorFlow 101: Introduction to Deep Learning online certification is created by Sefik Ilkin Serengil - Software Engineer, which is delivered by Udemy for the participants who are interested in learning the TensorFlow framework and concepts involved with artificial intelligence, machine learning, and data science.

TensorFlow 101: Introduction to Deep Learning online training is a self-paced program that offers 4 hours of digital lessons accompanied by downloadable learning resources and assignments which is aimed at the participants who want to acquire a foundational understanding of the concepts involved with deep learning from scratch. TensorFlow 101: Introduction to Deep Learning online classes discusses topics like deep neural networks, segmentation analysis, time series analysis, supervised learning, unsupervised learning, face recognition, machine learning models, and more.

The highlights

  • Certificate of completion
  • Self-paced course
  • 4 hours of pre-recorded video content
  • Learning resources
  • Assignments

Program offerings

  • Online course
  • Learning resources
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 499  ₹1,499
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Machine learning Knowledge of deep learning

After completing the TensorFlow 101: Introduction to Deep Learning certification course, participants will be introduced to the foundational concepts of deep learning as well as will acquire the knowledge of the functionalities of Tensorflow for deep learning and machine learning activities. In this deep learning course, participants will distinguish between classification and regression challenges using the features of supervised learning as well as will gain the skills to apply segmentation analysis using unsupervised learning and clustering. In this deep learning certification, participants will learn about concepts involved with time series analysis, face recognition, and deep neural networks as well as will acquire the knowledge of the techniques to build machine learning models.

The syllabus

Perceptrons

  • What is a Perceptron?
  • Hands-on Perceptron
  • Testing regular perceptron for XOR Gate

Introduction

  • Installing Tensorflow and Prerequisites on Windows
  • Jupyter notebook
  • Hello, TensorFlow! Building Deep Neural Networks Classifier Model
  • Building Deep Neural Networks Classifier for both AND and OR gates

Reusability in TensorFlow

  • Restoring and Working on Already Trained Deep Neural Networks In TensorFlow
  • Importing Saved TensorFlow DNN Classifier Model in Java

Monitoring and Evaluating

  • Monitoring Model Evaluation Metrics in TensorFlow and TensorBoard

Building regression and time series models

  • Building a DNN Regressor for Non-Linear Time Series in TensorFlow
  • Visualizing ML Results with matplotlib and Embedding in TensorBoard
  • Importing Saved DNNRegressor Model in Java

Building Unsupervised Learning Models

  • Unsupervised learning and k-means clustering with TensorFlow
  • Applying k-means clustering to n-dimensional datasets in TensorFlow

Tuning Deep Neural Network Models

  • Optimization Algorithms in TensorFlow
  • Activation Functions in TensorFlow
  • Applying different optimization algorithms while running regressor for sine wave
  • Applying different activation functions for sine wave example

Consuming TensorFlow via Keras

  • Installing Keras
  • Building DNN Classifier with Keras
  • Storing and restoring a trained neural networks model with Keras

Advanced applications

  • Handwritten Digit Recognition Using Neural Networks
  • Handwritten Digit Recognition Using Convolutional Neural Networks with Keras
  • Transfer Learning: Consuming InceptionV3 to Classify Cat and Dog Images in Keras
  • Tips and Tricks for Transfer Learning
  • Autoencoders
  • Face Recognition

Instructors

Mr Sefik Ilkin Serengil

Mr Sefik Ilkin Serengil
Data Scientist
Freelancer

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