Artificial Intelligence & Deep Learning with Tensorflow Online Course
EdUnbox’s Artificial Intelligence & Deep Learning Course with Tensorflow helps you to master the TensorFlow, deep learning libraries, CNN, GPU in deep learning, RBM, TensorFlow-Code, hyperparameters, RNN, transfer learning, API, recurrent neural networks, and Perceptron in CNN through hands-on projects. Study AI & deep learning in this certification course with Tensorflow which is carefully created by industry experts with real-time case studies. You will learn concepts of deep learning, execute algorithms of deep learning, and create networks of artificial neural.
About this Online Training Course:
EdUnbox’s Artificial Intelligence & Deep Learning with Tensorflow Course provides the all-inclusive Deep Learning training that will assist you to work on artificial intelligence. In this program you will also learn the skill of the various facts of vectorization, binary classification, artificial neural networks logistic regression with neural network attitude, administered and unsupervised learning comprising scripting of machine learning uses with python. It is among the most exhilarating and a favorable section of AI and machine learning technologies is Deep Learning.In deep learning advancements can be observed through smartphone applications, generating effectiveness in the power grid, driving enhancements in healthcare sector, enhancing agricultural yields, and assisting us to discover solutions to climate variation.
What will you learn in this Artificial Intelligence & Deep Learning with Tensorflow online Course?
This EdUnbox Artificial Intelligence & Deep Learning with Tensorflow training Course will enable you to understand the fundamentals of Deep Learning techniques, a neural network with training data, Tensor processing unit and TensorFlow, machine learning with python language, real-time projects in recommender systems and others, uses of deep learning in image recognition, NLP and more, administered and unsupervised training methodology, neural networks convolutional and its utilization and understanding an Artificial Neural Network. This course covers the following topics:
- Introduction to Artificial Intelligence and Deep Learning
- Enhance and troubleshoot deep learning models
- Craft your own project on DL
- Comprehend the TensorFlow & Tensor processing unit
- Comparative analysis among artificial intelligence, deep learning and machine learning
- Scope of Machine learning
- Execution of deep learning algorithms
Who should go for this Artificial Intelligence & Deep Learning with Tensorflow Certification Course?
It is ideal for professionals passionate for Deep Learning to purse TensorFlow and Python learning. Similarly, it is optimal choices who want pursue their career as a Deep Learning Engineer. Below are the professionals who will benefit with this course:
- Analytics Managers who are managing analysts team
- Analysts trying to comprehend the concepts of Deep Science theories
- Developers who are trying to become a Data Scientist
- Befitting for Business Analyst attempting comprehend Deep Learning Techniques
- Information Architects enhancing their knowledge base in predictive analytics
What are the prerequisites for this Online Certification Course?
Professionals in this online certification course of deep learning should have at least understanding with programming fundamentals and aware of the fundamentals of statistics and mathematics
- According to Indeed.com, The Average Salary of an Artificial Intelligence Engineer in the USA ranges from approximately $134,135 per year to $169,930 per year.
- Deep Learning is today’s most fast-tracking and favorable fields, in all the available technologies in the IT sector today.
- To become skilled in this tech, you require a well-thought-out training with the up-to-date expertise in accordance with the current industry necessities and standard practices.
- Moreover robust theoretical comprehension, you will get an opportunity to work on numerous projects on data utilizing distinct architectures of neural network as a portion of key strategy.
- Furthermore, you get assistance from a professional in Deep Learning who is well aware of current working standards in the industry with help of hands-on projects.
1. Introduction to TensorFlow
- Overview of TensorFlow
- Activation Functions
- Important Parameters of Perceptron
- TensorFlow code-basics
- Graph Visualization
- Step by Step – Use-Case Implementation
- Illustrate Perceptron
- Training a Perceptron
- Constants, Placeholders, Variables
- Creating a Model The way Deep Learning works
2. Introduction to Deep Learning
- Learn the cases usage of Deep Learning
- Assessment of Machine Learning in the below mentioned aspects:
- Reinforcement Learning
- Underfitting and Overfitting
- Drawbacks of Machine Learning
- Causes to learn Deep Learning
- Deep Learning Introduction
- Benefits of Deep Learning over Machine learning
- Aspects of Deep Learning
3. Multi-layered Neural Networks
- What is Multi-Layer Network?
- Concept of Deep neural networks
- Multi-layer perceptron
- Capacity and over fitting
- Neural network hyper parameters
- Logic gates
- The numerous activation functions in neural networks like Sigmoid, ReLu and Softmax
- Hyperbolic functions
- Back propagation
- Forward propagation
4. Keras API
- Keras high-level neural network for working on top of TensorFlow
- Learn complex multi-output models
- Comprising models by means of Keras
- Batch normalization
- Deploying Keras with TensorBoard
- Neural network training process customization
- Sequential and functional composition
5. GPU in Deep Learning
- What is GPUs?
- How they differ from CPUs?
- Significance of GPUs in training Deep Learning Networks
- Forward pass and backward pass training technique
- GPU constituent with simpler core and concurrent hardware
6. Autoencoders & Restricted Boltzmann Machine (RBM)
- Introduction to RBM and autoencoders
- Deploying it for deep neural networks
- Collaborative filtering using RBM
- Characteristics of autoencoders
- Uses of autoencoders
7. RNN: Recurrent Neural Networks
- Learn about 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
- Basic RNN cell
- Unfolded RNN
- Training in RNN
- Dynamic RNN
- Time-series predictions
8. Deep Learning applications
- Image Processing
- Natural Language Processing
- Speech Recognition
- Video Analytics
9. CNN: Convolutional Neural Networks
- Intro to Convolutional Neural Network
- Learn about the architecture of CNN
- Usage cases of CNN
- Learn about pooling layer
- Visualization using CNN
- Ways to fine-tune a Convolutional Neural Network
- Know about Transfer Learning and understanding Recurrent Neural Networks
- Feature maps
- Kernel filter
- Pooling, deploying convolutional neural network in TensorFlow
10. DNN: Deep Neural Networks
- Mapping the human mind with Deep Neural Networks
- Numerous building blocks of Artificial Neural Networks
- Architecture of DNN
- Concept of reinforcement learning in DNN
- Various parameters, layers, activation functions and optimization algorithms in DNN
11. Chatbots- Automated conversation bots using one of the descriptive techniques
- IBM Watson
- Google API AI
- Microsoft’s Luis
- Amazon Lex
- Open-Close Domain Bots
- Sequence to Sequence model (LSTM)
12. AI Deep Learning Project- 1
- Image recognition with TensorFlow
- Creating a strong deep learning model to know the exact object on the internet dependent on the user search for the image.
- Constructing Convolutional Neural Network using TensorFlow
- Convolutional, Dense & Pooling layers of CNNs
- Filtering the images based on user queries
13. AI Deep Learning Project- 2
- Building an AI-based Chatbots
- Encompasses creating the Chatbots by means of AI and Google TensorFlow.
- Splitting user inquiries into sections
- Building neural networks with TensorFlow
- Natural language processing
EdUnbox is pleased to provide this all-inclusive certification course for comprehending the Artificial Intelligence & Deep Learning Course with Tensorflow. Currently, you can avail the most desired positions in private sector in multi-national companies, national companies and PSUs with this valuable skillset. You also get a hands-on experience with assignments as part of the training that has remarkable effects in the current industry landscape assisting to fast-track your career efficiently.
Towards the completion of this training program, you will participate in the real-time projects and quizzes that will prepare you for questions in the certification examination and help you to score well in this exam.EdUnbox Course Completion Certificate will be awarded on the completion of projects on the basis of trainer reviews and on scoring 50% minimum marks in the quiz. EdUnbox certification is well recognized among leading corporate brands in a wide range of industries and verticals including Fortune 500 companies. Let the community know about your achievement and become certified today! Advance your career with our Artificial Intelligence & Deep Learning Course with Tensorflow Training course.
Payments can be made using any of the following options. You will be emailed a receipt after the payment is made.
- Visa Credit or Debit Card
- American Express
- Diner’s Club
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