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Deep Learning Online Training

Deep Learning Online Training is designed to foster the data analysis, digitalized work process, and machine learning. It is the branch of machine learning which uses the neural networks and abundant data as input to provide accurate results. Deep learning is also a part of artificial intelligence which is surpassing human intelligence in some cases. The concepts covered under Deep Learning Course include neural networks, back propagation, convolution neural networks, python programming, recurrent neural network, and gradient descent. Deep learning filters the data as images, sound, text for further classification. Human brain process the information with cognitive intelligence which is declared by cognitive neural scientists. This concept is integrated with technology in deep learning by learning the layers and each layer will take note from the previous layer before processing. Supervised learning classifies the task, semi supervised learning uses the labeled information and unlabeled information, unsupervised learning deals with unlabelled information and works with the relationships among the data. Deep learning makes the process speedy and delivers the result with accuracy. Deep learning architectures are used in different tasks like image recognition, speech recognition, Medical image processing, social network, self driving cars, movie recommendations, fraud detection for financial operations, and drug finding related to the medical image processing. Deep Learning Training introduces essential libraries like distributed keras, TensorFlow, pyTorch, and Apache MXNet. After the Deep Learning Course the learners can appear for the Deep Learning Certification by IBM or Deep Learning Training Certification from Microsoft or AWS Certified Machine Learning- specialty Certification or Microsoft Certified Azure AI Engineer Associate. GangBoard trainers provide clear guidance for procuring the Deep Learning Certification.

Best Deep Learning Online Training

GangBoard offers the Best Deep Learning Training with real time projects from the business applications which provide the ideal use cases. Artificial intelligence has its presence in recommender systems, visual search, user shopping, retail analytics, object detection, machine translation, text classification, document summarization and data extraction. Neural networks demand for more data than machine learning algorithms. Thousands of neurons work on the embedded behavior of the data which gives the result which is said as the black box result sometimes. Predictive models need more data and training for the different domains in which they need to perform. We understand the challenging part of the technology and that is why framed the syllabus as well as the project as job oriented training. As a sign of hype, a Deep learning algorithm is used in machine learning to getting accurate results. Domain knowledge is essential for taking the decisions which are the job of feature engineering. Deep learning works like a human brain in analyzing the information needed for different types of domain. The self-life of data is less and that is why it is used at the right time for productive reasons. 80 percent of the data available for the data analysis is unstructured data which gives accurate decisions than structured data. Training the machines with deep learning algorithms is not like developing an application for the business. Deep Learning Training is more about preparing the machine for domain knowledge.
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35 Hours
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Business Intelligence
365 Days
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About Course

In this Deep Learning Online Course the learners will learn about building models and these models can be learned through the jypyter notebooks or Microsoft Azure notebooks platform which run on your Linux or windows. The different types of the deep neural networks like CNN, LSTM, RNN and MLP are learned through this course.

Deep Learning Online Course will explain about the deep learning algorithm, real world scenarios, and problem solving skills.

Main Objective of this course:

  • Learn about the working of the sequential data.
  • Understand about different domains and the respective algorithms used for each domain.
  • Solve the problems using the deep learning algorithm.
  • Learn about the memory networks, deep recurrent, and the Turing machines.
  • After the Deep Learning Online Course the learner will get an idea about the different convolution networks, Boltzmann machines, and auto encoders.
  • After the Deep Learning Online Training, learners will understand about the projects in which deep learning can be applied and in which deep learning is not suitable.

The case studies with a connection to the real world problems will give opportunity to understand the concepts of Deep Learning better through the Deep Learning Online Training. This Deep Learning Online Course help for the better understanding of the smart robots, audio database, and text formats which we use in the business.

Deep learning Training does require the mathematical concepts, data modeling, statistics, and probability. Especially mathematical basics like algebra, probability, statistics and calculus are essential for understanding the deep learning. Basic knowledge of mathematics is helpful in understanding the concepts of deep learning. Students with mathematical back ground or statistical background can go for this deep learning course.

Introduction to Deep Learning

The steps involved in training the machines with deep learning are to prepare the input and output of the problem, gather data for the input, chose an evaluation protocol, and chose other protocols also, split the data as per the training, develop a model, and tune the model for the best performance. Each domain requires different data and different models for training the machines. Deep Learning Training with GangBoard will opt for the different domains as per the interest of the learners experiment with the application of the concept.

Classifier, several features, and statistical characteristics are the basis on which the sample size of the data is calculated to use a Deep learning algorithm. Our human brains have loads of labeled information which we have acquired with the experience but machines are not introduced to data. So, if we want to create intelligence like the human brain then loads of data is required.

Data in large numbers are needed for training and creating models. Sensors need a variety of data to understand the problem and find a solution to the problem. These data are acquired from open source datasets, synthetic data sets, built-in image annotators; data collected through BPO, and customized datasets.

As there is a huge need for data the future work process will be centralized to collect the data for analysis. Data Science, Machine learning, RPA, and deep learning are technologies that demand big data. Inside every SDK deep learning will constitute a place to improve the performance of data. For designing also Deep learning will empower different product design. The use cases for similar learning will be handled with an option called transfer learning. Deep learning can be reused with different reusable components. The tools of deep learning will create a pluggable algorithm library for APIs. Deep learning will be supported by Tensor flow and Spark in many projects and adoption will increase more. In future, many jobs are created with a job description of Deep Learning Course Certification. Undergoing Deep Learning Training is the wise choice for getting more opportunities and career growth in the future.

Deep learning aid for digitalized environment and they work fast as a digital worker. Deep learning is the best solution for data analysis and digital work which leads to a reduction in the cost. For the repetitive tasks in the software projects Deep learning provides accurate solutions. Deep learning help with the quality results in the organizations. Deep learning improves productivity and intelligence in different types of business. When pursuing the Deep Learning Course our trainers provide a real market update regarding the technology which makes the learners as industry-ready.

Upcoming Batches

Start Date End Date Time (EST) ( UTC -5) Day
25 Oct 2019 22 Nov 2019 (09:30 PM - 11:00 PM) Fri,Sat
26 Oct 2019 23 Nov 2019 (09:30 AM - 11:00 AM) Sat,Sun
28 Oct 2019 25 Nov 2019 (09:30 PM - 10:00 PM) Mon-Fri
29 Oct 2019 26 Nov 2019 (11:00 AM - 11:30 AM) Tue-Sat
29 Oct 2019 26 Nov 2019 (09:30 AM - 10:00 AM) Tue-Sat

Deep Learning Online Training Reviews

FAQ

Detailed installation of required software will be displayed in your LMS. Our support team will help you to setup software if you need assistance. Hardware requirements need to be fulfilled by participants.

No worries. It might happen. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. And if required you can even attend that topic if any other live batches.

Top-notch professionals in that field who understands how to convey things in technical as well as subject matter experts.

We offer this course in “Live Instructor-Led Online Training” mode. Through this way you won’t mess anything in your real-life schedule. You will be shared with live meeting access while your session starts.

You can get a sample class recording to ensure you are in right place. We ensure you will be getting complete worth of your money by assigning a best instructor in that technology.

We are absolutely loved to talk in-person about group training (or) corporate training. So, please get in touch with our team through “Quick Enquiry”, “Live Chat” or “Request Call-back” channels.

Payments can be made using any of the following options and a receipt of the same will be issued to you automatically via email.

  1. Visa Debit Card / Credit Card
  2. American Express
  3. Master Card, Or
  4. PayPal

You can reach us through  +91-755 022 6991 / +91-984 025 8966. Or you can share your quires through enq@gangboard.com. Estimated turnaround time will be 24 hours for emails.AWS Certified Advanced Networking Specialty Training

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GangBoard 5 Star Rating: Recommended 5 out of 5 based on 1432 ratings.