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TensorFlow Certification

TensorFlow Training

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Duration : 2 Months
Daily : 2 hours
Overview of TensorFlow Course Online

Sipexe offers job-oriented and industry-focused TensorFlow Course Online. This course aims to teach you all the skills required to create neural networks and how to train, evaluate, and optimize TensorFlow and pass the TensorFlow certification. TensorFlow is machine learning framework from Google for designing, and building deep learning models. Can use TensorFlow library to perform numerical computations, which in itself seems like nothing special. These calculations are performed using a data flow diagram. In this diagram, nodes represent mathematical operations, and ribs represent data. Usually, a multidimensional data field or tensor is used to connect these edges. TensorFlow experts can earn up to $204,000 per year, with an average salary of $1,31,046 according to 2021 statistics. You can establish yourself in various roles such as Machine learning engineer, Machine Learning software engineer, and many other vital posts.

This course focuses on using TensorFlow's adaptability and ease of use to create and deploy machine learning models. You will learn about the TensorFlow API and explore critical components of TensorFlow through real-world cases and hands-on exercises. We will demonstrate how to work with datasets and Features sets, learn how to design and create a TensorFlow input pipeline, practice loading CSV data, NumPy arrays, text data, and images with it. Data. The TensorFlow classes are designed to give you the best virtual learning environment. By the end of the course, you will be proficient in developing and deploying TensorFlow models. 

TensorFlow Fundamental Key Features

  • Installing and Configuring Tensorflow
  • Tensorflow Fundamentals
  • Top Tensorflow interview questions
  • Tensorflow tutorial for self-study
  • Tensorflow resume preparation
  • 24* seven support
  • Flexible schedule
  • One on One session
Who should take the TensorFlow Course?

This course is ideal for anyone who wants to clear the TensorFlow developer exam, apart from developers, data scientists, and students who wish to enhance their machine learning skills or pursue a Tensorflow career.

Specifications
  • Free Demo
  • 100% job Assistance
  • Flexible Timing
  • Realtime Project Work
  • Learn From Experts
  • Get Certified
  • Place your career
  • Reasonable fees
  • Access on mobile and Tv
  • High-quality content and Class videos
  • Learning Management System
  • Full lifetime access
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Course Curriculum
  • Introduction To Deep Learning
    • Deep Learning: A revolution in Artificial Intelligence
    • Limitations of Machine Learning
    • Discuss the idea behind Deep Learning
    • Advantage of Deep Learning over Machine learning
    • The Math behind Machine Learning: Linear Algebra
    • Scalars
    • Vectors
    • Matrices
    • Tensors
    • Hyperplanes
    • The Math Behind Machine Learning: Statistics
    • Probability
    • Conditional Probabilities
    • Posterior Probability
    • Distributions
    • Samples vs Population
    • Resampling Methods
    • Selection Bias
    • Likelihood
  • Review of Machine Learning Algorithms
    • Regression
    • Classification
    • Clustering
    • Reinforcement Learning
    • Underfitting and Overfitting
    • Optimization
    • Convex Optimization
  • Fundamentals of Neural Networks
    • Defining Neural Networks
    • The Biological Neuron
    • The Perceptron
    • Multi-Layer Feed-Forward Networks
    • Training Neural Networks
    • Backpropagation Learning
    • Gradient Descent
    • Stochastic Gradient Descent
    • Quasi-Newton Optimization Methods
    • Generative vs Discriminative Models
    • Activation Functions
    • Linear
    • Sigmoid
    • Tanh
    • Hard Tanh
    • Softmax
    • Rectified Linear
    • Loss Functions
    • Loss Function Notation
    • Loss Functions for Regression
    • Loss Functions for Classification
    • Loss Functions for Reconstruction
    • Hyperparameters
    • Learning Rate
    • Regularization
    • Momentum
    • Sparsity
  • Fundamentals Of Deep Networks
    • Defining Deep Learning
    • Defining Deep Networks
    • Common Architectural Principals of Deep Networks
    • Reinforcement Learning application in Deep Networks
    • Parameters
    • Layers
    • Activation Functions – Sigmoid, Tanh, ReLU
    • Loss Functions
    • Optimization Algorithms
    • Hyperparameters
  • Introduction To TensorFlow
    • What is TensorFlow?
    • Use of TensorFlow in Deep Learning
    • Working of TensorFlow
    • How to install Tensorflow
    • HelloWorld with TensorFlow
    • Running a Machine learning algorithms on TensorFlow
  • Convolutional Neural Networks (CNN)
    • Introduction to CNNs
    • CNNs Application
    • Architecture of a CNN
    • Convolution and Pooling layers in a CNN
    • Understanding and Visualizing a CNN
    • Transfer Learning and Fine-tuning Convolutional Neural Networks
  • Recurrent Neural Networks (RNN)
    • Introduction to RNN Model
    • Application use cases of RNN
    • Modelling sequences
    • Training RNNs with Backpropagation
    • Long Short-Term memory (LSTM)
    • Recursive Neural Tensor Network Theory
    • Recurrent Neural Network Model
  • Restricted Boltzmann Machine(RBM) And Autoencoders
    • Restricted Boltzmann Machine
    • Applications of RBM
    • Collaborative Filtering with RBM
    • Introduction to Autoencoders
    • Autoencoders applications
    • Understanding Autoencoders
    • Variational Autoencoders
    • Deep Belief Network
TensorFlow Certification FAQ's

TensorFlow Serving is an adaptable machine learning model designed for production environments. TensorFlow Serving allows you to develop new algorithms and experiments while keeping the same server architecture and API.

The TensorFlow organization provides a TensorFlow developer certificate. It is an online exam. Our institute provides complete guidance in preparing you for clearing the TensorFlow examination.

We will reschedule the session for another day or provide you with a recording of the session and materials for TensorFlow's self-study.

Yes, we offer job placement services.

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Contant Info
  • 651 N Broad St, Middletown, DE 19709, United States

  • info@sipexe.com
  • +1-302-208-0020
  • sipexe.com
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