Deep Learning Online Training Course

Machine Learning concerned with Algorithms | Deep Learning

deep learning online training
Tableau Online Training
Average Rating: 4.6
Votes: 101
Reviews: 83

Overview : Depp Learning Essentials

Deep learning is an exciting branch of machine learning that uses data,lots of data, to teach computers how to do things only humans were capable of before. QaTrainingHub offers the best faculty to teach Deep Learning who is an RealTime Industry Expert & solving the problem of perception. Recognizing what's in an image, what people are saying when they are talking on their phone, helping robots explore the world and interact with it.

Deep learning is emerge as a central tool to solve perception problems in recent years. It's the state of the art having to do with computer vision and speech recognition. But there's more. Increasingly, people are finding that deep learning is a much better tool to solve problems like discovering new medicines, understanding natural language, understanding documents, and for example, ranking them for search.

You will also train your first deep network and you'll also learn to apply regularization techniques to train even bigger models with our qatraininghub Team. deep dive into images and convolutional models.all about text and sequences in general. We'll train embeddings and recurrent models. This is going to be a very hands-on & professional course.you'll be able to apply all this knowledge to new problems entirely by yourself with a handful of lines of code.

Deep Learning Online Training Course Content

    Advanced Data Science
  • Review of data analytics life cycle
  • Data analytics life cycle
  • Summary of per-phase techniques
  • Introduction to deep learning & unstructued data analysis
  • Types of unstructured data
  • Use cases for unstructured data analytics
  • How do you handle unstructured data for classification and regression analytics?
  • Nature of features in image, text, voice, audio & video data
  • What is deep learning?
  • Why do we care about deep learning now?
  • Benefits of deep learning
  • Limitations of deep learning
  • Applications of deep learning
  • Python for data analytics
  • Setting up python environment
  • Data types
  • Control statements
  • Python libraries for data analytics
  • Pre-deep learning approaches for image based analytics
  • Image preprocessing
  • Handicrafted Feature extraction for image
  • Feature extraction
  • Color
  • SIFT
  • HOG
  • Edges
  • Keypoints
  • Bag of word feature representation
  • Bag of word with spatial pyramids
  • Part based feature representation
  • Solving Kaggle problem: Detecting cats & dogs
  • Pre-deep learning approaches for text based analytics
  • Text preprocessing
  • Handicrafted Feature extraction for text
  • Feature extraction
  • Unigrams
  • Bigrams
  • Trigrams
  • Skipgrams
  • Bag of word feature representation
  • Solving Kaggle problem: Sentiment analysis on movie reviews
  • Neural networks for machine learning
  • Modelling human brain learning to machines
  • Idea of neuron
  • Activation functions
  • Concept of neural network
  • Perceptron
  • Perceptron model
  • Perceptron learning
  • Multi-layer neural network
  • Multi-layer NN model
  • NN learning
  • Why are neural networks special?
  • Neural networks for supervised learning
  • Neural networks for unsupervised learning
  • Deep neural networks for machine learning
  • Neural network vs Deep neural network
  • Deep learning algorithms
  • Sparse coding
  • Deep belief networks
  • Deep sparse auto encoders
  • Speeding up deep learning: GPU based learning
  • Practical deep learning networks
  • Fully connected deep networks(DNN)
  • Convolutional deep networks(CNN)
  • Recurrent deep networks(RNN/LSTM)
  • Deep learning frameworks
  • Theano
  • Caffe
  • Torch
  • TensorFlow
  • Applying deep learning approaches for text based analytics
  • Deep networks for text analysis
  • Kaggle Problem:Named entity recognition
  • Kaggle Problem:Sentiment analysis on movie reviews
  • Applying deep learning approaches for image based analytics
  • Deep networks for image analysis
  • Kaggle Problem:Detecting cats & dogs
  • Kaggle Problem:Face recognition

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