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**AI and Deep Learning with TensorFlow: https://www.edureka.co/ai-deep-learning-with-tensorflow **
This video on Deep Learning Projects will provide you with a list of the top open-source deep learning projects you must try in 2019.

Lung Cancer Detection: https://github.com/ddhaval04/Lung-Cancer-Detection
Google Tulip: https://github.com/GoogleCloudPlatform/tulip
Detectron: https://github.com/facebookresearch/Detectron
WaveGlow: https://github.com/NVIDIA/waveglow
Image Enlarging: https://ai.google/research/pubs/pub45953/
OpenCog: https://opencog.org/
DeepMiminc: https://github.com/xbpeng/DeepMimic
ImageOutpaninting: https://github.com/bendangnuksung/Image-OutPainting
IBM Watson: https://www.ibm.com/watson
Check out our playlist for more videos: http://bit.ly/2taym8X

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#DeepLearningProjects

How it Works?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!
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About the course:

Edureka's Deep Learning in TensorFlow with Python Certification Training is curated by industry professionals as per the industry requirements & demands. You will master the concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn. The course has been specially curated by industry experts with real-time case studies.

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Objectives:

Deep Learning in TensorFlow with Python Training is designed by industry experts to make you a Certified Deep Learning Engineer. The Deep Learning in TensorFlow course offers:
In-depth knowledge of Deep Neural Networks
Comprehensive knowledge of various Neural Network architectures such as Convolutional Neural Network, Recurrent Neural Network, Autoencoders
Implementation of Collaborative Filtering with RBM
The exposure to real-life industry-based projects which will be executed using TensorFlow library
Rigorous involvement of an SME throughout the AI & Deep Learning Training to learn industry standards and best practices
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Why should one go for this course?

Deep Learning is one of the most accelerating and promising fields, among all the technologies available in the IT market today. To become an expert in this technology, you need structured training with the latest skills as per current industry requirements and best practices.

Besides strong theoretical understanding, you will be working on various real-life data projects using different neural network architectures as a part of the solution strategy.

Additionally, you will receive guidance from a Deep Learning expert who is currently working in the industry on real-life projects.

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Skills that you will be learning:

Deep Learning and TensorFlow Concepts
Working with Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN)
Proficiency in Long short-term memory (LSTM)
Implementing Keras, TFlearn, Autoencoders
Implementing Restricted Boltzmann Machine (RBM)
Knowledge of Neural Networks & Natural Language Processing (NLP)
Using Python with TensorFlow Libraries
Perform Text Analytics
Perform Text Processing
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Who should go for this course?

The TensorFlow with Python Training is for all the professionals who are passionate about Deep Learning and want to go ahead and make their career as a Deep Learning Engineer. It is best suited for individuals who are:

Developers aspiring to be a 'Data Scientist'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Deep Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused on one industry or skill set, it can be used by anyone to enhance their portfolio.

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*** Machine Learning Podcast - https://castbox.fm/channel/id1832236 ***
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शिक्षा - Education
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