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- Duration / Course length: 1 To 2 Months Start now
- Certificates:
- Course delivery: This course is delivered in video format
Course details
Caffe2, open-sourced by Facebook, is a simple, flexible framework for efficient deep learning. This course will teach you about Caffe2 and show you how to train your deep learning ;Note: Hard copy material is not applicable for this course.
Why should one take this certification?
In this online course, you will learn the foundations of Deep Learning, understand how to build neural networks and develop an understanding of convolutional networks, RNNs, Adam, Dropout, BatchNorm and ;
You’ll be working on various projects throughout this online course with a focus on how to train and manipulate a deep neural network effectively. All these will be practiced in Caffe2 using Python programming languages.
Who will benefit from taking this certification?
Job seekers looking for employment in various IT companies, PSUs or MNCs. Certification in Deep learning with Caffe framework benefits Data Science professionals, students and professionals across various Industries.
Benefits of Certification
- Government certification
- Certification valid for life
- Lifelong e-learning access
- Learning Hours: 12+ hrs
How It Works
- Select Certification & Register
- Receive Online e-Learning Access (LMS)
- Take exam online anywhere, anytime
- Get certified & Increase Employability
- Duration: 60 minutes
- No. of questions: 50
- Maximum marks: 50, Passing marks: 25 (50%).
- There is NO negative marking in this module.
- Online exam.
TABLE OF CONTENT
Setting Up Caffe2
- Set Up Caffe2 on Linux
- Understanding the Caffe2 Architecture
- Transitioning from Machine Learning to Deep Learning
- Running an Image Classifier Using Caffe2
- Learn about Matrices Using Python – NumPy
- Understanding and Implementing Logistic Regression and Neural Networks
- Understanding and Implementing Deep Neural Networks
- Caffe2 Introduction
- Caffe2 Python Wrapper
- Mathematical Operators in Caffe2
- Network Creators and Assisters in Caffe2 – Part 1
- Network Creators and Assisters in Caffe2 – Part 2
- Network Creators and Assisters in Caffe2 – Part 3
- How Machines Learn to See!
- Introduction to Convolutional Neural Networks
- Implement a Convolution Layer Using Caffe2
- Pooling Layer and Dropout in Caffe2
- Role of Activation Functions in Solving Non-Linear Optimization
- Machine Learning Strategy
- How to Perform Data Selection, Preparation, and Processing
- Regularization of Neural Networks
- Optimizing Neural Networks
- Optimization Algorithms
- Sequence Learning
- Introduction to Recurrent Neural Networks
- LSTMs – A Special Case of RNNs
- Learning about Word Embeddings
- Introduction to Augmented Recurrent Neural Networks
- Why Deep Learning?
- Machine Learning Categories
- Why Caffe2?
- Install and Set Up Caffe2
- Build a Caffe2 Docker
- Definition of a Computational Graph Through Examples
- Introduce Workspace, Operators, and Nets
- Working with Computational Graphs
- Housing Price Prediction
- Representing a Linear Regression Model in a Computational Graph
- Training Procedure
- Training a Linear Regression Model
- Fashion Product Recognition Problem
- What Is Supervised Learning?
- What Is Transfer Learning?
- Model Zoo in Caffe2
- Fine-Tune a Model for Recognizing Fashion Products
- Chatbot Customer Service
- What Is Sequence-to-Sequence Learning?
- What Are RNNs and LSTMs?
- Training an RNN-Based Model to Write like Shakespeare
- Why Deep Reinforcement Learning?
- What Is Deep Reinforcement Learning?
- What Is Deep Q-Network?
- Training a Deep Q- Network for Solving the Cart-Pole Problem
- AI on Mobile Devices Using Face ID
- Challenges in Running AI Models on Mobile Devices
- SequeezeNet
- Deploy SequeezeNet on a Mobile Device
Eligibility / Requirements
Anyone can apply for the online certification
Job roles this course is suitable for:
Data Analyst , Data & AI Consultant , Computer Vision EngineerAbout Vskills
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