Course description
Working With TensorFlow
Working with TensorFlow explores algorithms, machine learning, and data mining concepts, and how TensorFlow implements them, working in a hands-on manner. This “skills-centric” course is about 50% hands-on lab and 50% lecture, integrating practical hands-on labs designed to reinforce fundamental skills, concepts and best practices introduced throughout the course. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern "on-the-job" into every classroom and hands-on project.
Working in a hands-on learning environment led by our expert team, students will explore:
- Core Deep Learning and Machine Learning math essentials
- TensorFlow Overview and Basics.
- TensorFlow Operations
- Neural Networks With TensorFlow
- Deep Learning With TensorFlow
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Who should attend?
This in an intermediate-level course is geared for experienced developers or others (with prior Python experience) intending to start using and working with TensorFlow.
Students should have attended or have incoming skills equivalent to those in this course:
- Strong foundational mathematics in Linear Algebra and Probability; Matrix Transformation, Regressions, Standard Deviation, Statistics, Classification, etc.
- Basic knowledge of machine learning and deep learning algorithms
- Strong basic Python Skills
Training content
Machine Learning & Deep Learning Overview
- This is summary of ML/DL Concepts (from the class – Machine Learning & Deep Learning Fundamentals)
- Mathematical Concepts
- ML Overview
- DL Overview
TensorFlow – Overview & Basics
- TensorFlow – What is it? History & Background
- Use cases & Key Applications
- Machine Learning & Deep Learning Basics
- Environment, Configuration Settings & Installation
- TensorFlow Primitives
- Declaring Tensors
- Declaring Placeholders and Variables
- Working with Matrices
- Declaring Operations
- Operations in Computational Graph
- Nested Operations
- Multiple Layers
- Implementing Loss Functions
- Implementing Back Propagation
Machine Learning With TensorFlow
- Linear Regression Review
- Linear Regression Using TensorFlow
- Support Vector Machines (SVM) Review
- SVM using TensorFlow
- Nearest Neighbor Method Review
- Nearest Neighbor Method using TensorFlow
Neural Networks With TensorFlow
- Neural Networks Review
- Optimization and Operational Gates
- Working with Activation Functions
- Implementing One-Layer Neural Network
- Implementing Different Layers
- Implementing Multilayer Neural Networks
Deep Neural Networks With TensorFlow
- Models and Overview
- Single Hidden Layer
- Multiple Hidden Layer
- Convolutional Neural Network Overview & Implementation
- CNN Architecture
- Recurrent Neural Network Overview & Implementation
- RNN Architecture
TensorFlow: Additional Topics
- TensorFlow Extensions
- Scikit Flow
- TFLearn
- TF-Slim
- TensorLayer
- Keras
- Unit Testing
- Taking your implementation to production
- Other Misc Topics
Costs
- Price: $1,795.00
- Discounted Price: $1,166.75
Why choose Trivera Technologies LLC?
Over 25 years of technology training expertise.
Robust portfolio of over 1,000 leading edge technology courses.
Guaranteed to run courses and flexible learning options.
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Trivera Technologies
Trivera Technologies is a IT education services & courseware firm that offers a range of wide professional technical education services including: end to end IT training development and delivery, skills-based mentoring programs,new hire training and re-skilling services, courseware licensing and...