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Deep Learning with TensorFlow Training
Self-Paced, Live Online & Classroom Enterprise Training
Master core concepts of Deep Learning with Google's TensorFlow- a distributed scalable deep learning platform. Our Deep Learning course aids in building Deep Learning Models and Applications in TensorFlow, suitable for different business domains. Train your team on TensorFlow and Neural Nets to solve complex Organizational problems.
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Program Architect
Prof. Dr. James G. Shanahan
Dr. James has spent the past 25 years developing and researching cutting-edge artificial intelligent systems. He has (co)founded several companies, advises high-tech startups and held appointments at AT&T (Executive Director of Research), Turn Inc., Xerox Research, Mitsubishi Research, and at Clairvoyance Corp. He teaches at UC Berkeley and has published six books, more than 50 research publications, and has over 20 patents in the areas of machine learning and information processing.
What is Deep Learning Course about?
What are the objectives of Deep Learning Course ?
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Available Training Modes
Live Online Training
18 HoursClassroom Training
3 DaysCourse Outline Expand All
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- Data science & its importance
- Key Elements of Data Science
- Artificial Intelligence & Machine Learning Introduction
- Who uses AI?
- AI for Banking & Finance, Manufacturing, Healthcare, Retail and Supply Chain
- What makes a Machine Learning Expert?
- What to learn to become a Machine Learning Developer?
- Review of Machine Learning: Regression, Classification, Clustering, Reinforcement Learning, Underfitting and Overfitting, Optimization
- Deep Learning: A revolution in Artificial Intelligence
- What is Deep Learning?
- Advantage of Deep Learning over Machine learning
- 3 Reasons to go for Deep Learning
- Real-Life use cases of Deep Learning
- How Neural Networks Work?
- Various activation functions – Sigmoid, Relu, Tanh
- Perceptron and Multi-layer Perceptron
- What is TensorFlow?
- TensorFlow code-basics
- Graph Visualization
- Constants, Placeholders, Variables
- Creating a Model
- Step by Step - Use-Case Implementation
- Introduction to Keras
- Understand Neural Networks in Detail
- Illustrate Multi-Layer Perceptron
- Backpropagation – Learning Algorithm
- Understand Backpropagation – Using Neural Network Example
- MLP Digit-Classifier using TensorFlow
- Why Deep Networks
- Why Deep Networks give better accuracy?
- Understand How Deep Network Works?
- How Backpropagation Works?
- Illustrate Forward pass, Backward pass
- Different variants of Gradient Descent
- Types of Deep Networks
- Batch Normalization
- Activation and Loss functions
- Hyper parameter tuning
- Training challenges and techniques
- Optimizers, learning rate, momentum, etc.
- Introduction to CNNs
- CNNs Application
- Architecture of a CNN
- Forward propagation & Backpropagation for CNNs
- Convolution, Pooling, Padding & its mechanisms
- Understanding and Visualizing a CNN
- An overview of pre-trained models (AlexNet, VGGNet, InceptionNet & ResNet) and Transfer Learning
- Image classification using CNN
- Auto encoders
- Semantic segmentation
- YOLO
- Siamese Networks
- Object & face recognition using techniques above
- Sentiment Analysis
- Topic Summarization
- Topic Modelling
- Nltk, Gensim, vader, etc.
- Bag of Words and Tf-IDF
- Cosine Similarity of terms, documents concepts
- Text Cleaning and Preprocessing using Regex
- Tokenization, Stemming and Lemmatization
- Introduction to Sequential data
- Word embeddings and lang translation
- RNNs and its mechanisms
- Vanishing & Exploding gradients in RNNs
- Time series analysis
- LSTMs
- LSTMs with attention mechanism
- GRU
- What is Tensor board?
- Test vs Train set accuracy
- T-SNE
- Occlusion Experiment
- CAM, Saliency and Activation maps
- Visualizing Kernels
- Style transfer
- Introduction
- How GANs work?
- Applications of GANs (Generative adversarial networks)
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I attended the 3-day AngularJs training at SpringPeople. The trainer was an industry veteran with vast experience in the subject. Notably, the hands-on training, and the Q&A session stood out. Overall, I found SpringPeople a great place to learn with excellent facilities and great trainers. Would recommend SpringPeople to my colleagues and friends.
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I attended the training on API Design for Mulesoft. The sessions were well planned and value-laden. I benefited immensely from the hands-on experience enabled through virtual labs. I would like to specifically commend the efficiency of the support team who were always available to resolve my concerns.
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I attended the jQuery training batch, conducted by Mr. Vijay, an SME who did a thorough coverage of all the essentials. He took us through concepts such as jQuery animations, event handlers, plugins, and jQuery-UI by small programs, very easily. The sessions were useful and well structured. By the end of the training, I was well equipped to develop a SPA on Product Management System. Overall, the learning experience at SpringPeople was great!
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