We provide the best Deep Learning with TensorFlow Course that was designed by industry experts and structured by the latest model to make every concept match with current trends followed by industries. Candidates become experts with our concepts and methods the way we train with real-time projects from implementing deep learning algorithms and develop AI neural networks, and traverse layers of data abstraction to make you a deep understanding of the detailed programs.
Deep Learning Course (Duration : 8 Weeks)
Deep Learning Course Overview
Deep Learning is a subset of machine learning involved with algorithms stimulated by the structure and design of the intellectual called AI neural networks. NearLearn a leading deep learning training institute in Bangalore provides excellent courses demonstrate through our expert’s trainers will provide with hands-on-experience from basic to advance level that makes you build applications by covering all programs such as structured and hierarchical learning.
We have a strong background in teaching software programs like deep learning. We designed the courses with job oriented and goal setting, and result in the creation that provides instant value to any companies.
What you will receive with Deep Learning Training in Bangalore?
We have connected with companies that create awareness to update our programs based on requirements. You will start your deep learning training in Bangalore on the highly interactive platforms with support from industry experts, where you will learn the fundamentals through employing videos from Machine Learning specialists, application activities, and support.
You will travel to an extra appealing training formation with live speeches by our expert staff along with real-time projects. The trainers and lab assemblies are synced to guarantee that you receive a holistic learning expertise.
Why NearLearn for Deep Learning Classroom Course?
NearLearn holds 4 years of rich experience in providing classroom training for deep learning courses. We provide deep learning certification training in Bangalore on essential artificial intelligence topics.
This is a specialized course designed by our staff which will support you to get knowledge into the AI and Deep Learning field, with one of the most sought-after experiences. You will discover the support of Deep Learning, know how to create neural networks, and determine how to create strong Deep Learning-based AI designs managing Tensor Flow. You will serve on case studies on network vision, data processing, Image processing, Language analytics – Speech to text / Voice tonality. After the prosperous conclusion of this course, you will understand not only the ideas but also discover how it is implemented in the industry.
Course Intent
- Fundamentals of Deep Learning
- Various Deep networks
- Basics on Neural networks
- Application of Analytical mathematics on the data
- Discussion on Back propagation
- Knowledge on Auto encoders and variation Auto encoders
- Implement different Regression models
Who should take this Deep Learning Training Course?
- Analytics experts or candidates with a prior working experience of Data Science with Python, who are seeing Deep Learning certification to boost their career with the practical purpose of AI Deep Learning with TensorFlow.Experience with programming basics and fair understanding of the basics of statics mathematics is necessary.
Course Curriculum
Introduction to AI and Deep Learning
- Lecture1.1 Introduction to Deep LearningLecture1.2 Necessity of Deep Learning over Machine Learning.Lecture1.3 History and evolution of various deep learning algorithmsLecture1.4 AI and how is Deep Learning one of the paths to AI in the recent eraLecture1.5 Types of Machine Learning and Deep Learning
Lecture1.6 Why Deep Learning
Master Deep Network
Lecture2.1 Working of a Deep Network
Lecture2.2 What is Perceptron
Lecture2.3 What is Neuron
Lecture2.4 Sigmoid neuron
Lecture2.5 Activation functions
Lecture2.6 Cost function
Lecture2.7 Optimization
Lecture2.8 Dense networks
Lecture2.9 Regularization
Lecture2.10 Layered structures
Lecture2.11 Types of layers
Lecture2.12 Forward pass
Lecture2.13 Back propagation – chain rule and evaluation metrics
Lecture2.14 Gradient Descent
Lecture2.15 SGD (for a SoftMax classifier example)
Lecture2.16 Nestorov’s momentum
Lecture2.17 RMSProp
Lecture2.18 Adam
Objective on Neural networks using TensorFlow
Lecture3.5 Sessions
Lecture3.6 Graphs
Lecture3.7 Tensorboard
Lecture3.8 Implementation of a simple Perceptron in TensorFlow
Lecture3.9 Implementing a simple feed forward Neural Network in TensorFlow Lecture3.10 Various activation functions and their ranges
Lecture3.11 Pros and cons of Activation functions
Lecture3.12 Why to use specific activation function
Lecture3.13 When is the usage of activation function
Lecture3.14 What are the ones used in industry for specific tasks
Lecture3.15 Visualization of competition based craft and model results
Knowledge on CNN
Lecture4.1 Introduction to CNN (Convolutional Neural Networks)
Lecture4.2 Applications of CNN
Lecture4.3 CNN Architecture
Lecture4.4 Convolution
Lecture4.5 Pooling layers
Lecture4.6 CNN illustrations
Knowledge on RNN
Lecture5.1 Fundamentals of RNN (Recurrent Neural Network)
Lecture5.2 Applications of RNN
Lecture5.3 Modelling sequencing
Lecture5.4 Types of RNNs – LSTM, GRU
Lectures5.5 Recursive Neural Tensor Network Theory
Keras
Lecture6.1 Introduction of Keras
Lecture6.2 Understanding of Keras Model Building Blocks
Lecture6.3 Illustration of different Compositional Layers
Lectures6.4 Process based use cases’ implementations
TFlearn
Lecture7.1 Introduction of TFlearn
Lecture7.2 Understanding of TFlearn Model Building Blocks
Lecture7.3 Illustration of different Compositional Layers
Lectures7.4 Step-wise use-cases implementations
Different architectures and Performance improvements
Lecture8.1 ConvNets architecture
Lecture8.2 Performance evaluations
Lecture8.3 Hyperparameter search
Lecture8.4 Auto-monitoring of loss monitoring
Lecture8.5 Input pre-processing
Lecture8.6 Productionization of a deep learning pipeline
Lecture8.7 Cloud workspace set-up for designing a prototype
Building an AI application with Computer Vision
Lecture9.1 Application Building
Building an AI application - Natural Language Processing
Lecture10.1 Application Building
Course Schedule
Course ID
Course Name
Date
Price
Sample Certificates
IABAC Certificate
AI & Machine Learning Video
Programming Languages & Tools Covered
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Get in touch with us right away to discuss the ways in which the training solutions offered by Nearlearn can revolutionize your career.
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Manasa HG
Juniper Networks"Nearlearn is one of the best institutes for Data science and Machine learning training in Bangalore. Training sessions were very interactive. Trainer has very good subject knowledge,I am very satisfied with both Trainer & Institute."
Tushar Chorghe
GeBBS Healthcare Solutions"I would rate services provided by NearLearn as excellent because of the instructor and venue with the required discount for the course. The overall experience was very good and will surely look forward to attend many more trainings"