Course Outline
Introduction
Understanding the Fundamentals of Artificial Intelligence and Machine Learning
Understanding Deep Learning
- Overview of Basic Concepts in Deep Learning for Government
- Differentiating Between Machine Learning and Deep Learning for Government
- Overview of Applications for Deep Learning in Government Operations
Overview of Neural Networks for Government
- What are Neural Networks for Government
- Neural Networks vs Regression Models for Government
- Understanding Mathematical Foundations and Learning Mechanisms for Government
- Constructing an Artificial Neural Network for Government
- Understanding Neural Nodes and Connections for Government
- Working with Neurons, Layers, and Input and Output Data for Government
- Understanding Single Layer Perceptrons for Government
- Differences Between Supervised and Unsupervised Learning for Government
- Learning Feedforward and Feedback Neural Networks for Government
- Understanding Forward Propagation and Back Propagation for Government
- Understanding Long Short-Term Memory (LSTM) for Government
- Exploring Recurrent Neural Networks in Practice for Government
- Exploring Convolutional Neural Networks in Practice for Government
- Improving the Way Neural Networks Learn for Government
Overview of Deep Learning Techniques Used in Banking for Government
- Neural Networks for Government
- Natural Language Processing for Government
- Image Recognition for Government
- Speech Recognition for Government
- Sentiment Analysis for Government
Exploring Deep Learning Case Studies for Banking in a Government Context
- Anti-Money Laundering Programs for Government
- Know-Your-Customer (KYC) Checks for Government
- Sanctions List Monitoring for Government
- Billing Fraud Oversight for Government
- Risk Management for Government
- Fraud Detection for Government
- Product and Customer Segmentation for Government
- Performance Evaluation for Government
- General Compliance Functions for Government
Understanding the Benefits of Deep Learning for Banking in a Government Context
Exploring Different Deep Learning Libraries for Python for Government
- TensorFlow for Government
- Keras for Government
Setting Up Python with TensorFlow for Deep Learning in a Government Environment
- Installing the TensorFlow Python API for Government
- Testing the TensorFlow Installation for Government
- Setting Up TensorFlow for Development in a Government Setting
- Training Your First TensorFlow Neural Net Model for Government
Setting Up Python with Keras for Deep Learning in a Government Environment
Building Simple Deep Learning Models with Keras for Government
- Creating a Keras Model for Government
- Understanding Your Data for Government
- Specifying Your Deep Learning Model for Government
- Compiling Your Model for Government
- Fitting Your Model for Government
- Working with Your Classification Data for Government
- Working with Classification Models for Government
- Using Your Models for Government
Working with TensorFlow for Deep Learning in Banking for Government
- Preparing the Data for Government
- Downloading the Data for Government
- Preparing Training Data for Government
- Preparing Test Data for Government
- Scaling Inputs for Government
- Using Placeholders and Variables for Government
- Specifying the Network Architecture for Government
- Using the Cost Function for Government
- Using the Optimizer for Government
- Using Initializers for Government
- Fitting the Neural Network for Government
- Building the Graph for Government
- Inference for Government
- Loss for Government
- Training for Government
- Training the Model for Government
- The Graph for Government
- The Session for Government
- Train Loop for Government
- Evaluating the Model for Government
- Building the Eval Graph for Government
- Evaluating with Eval Output for Government
- Training Models at Scale for Government
- Visualizing and Evaluating Models with TensorBoard for Government
Hands-on: Building a Deep Learning Credit Risk Model Using Python for Government
Extending Your Company's Capabilities in a Government Setting
- Developing Models in the Cloud for Government
- Using GPUs to Accelerate Deep Learning for Government
- Applying Deep Learning Neural Networks for Computer Vision, Voice Recognition, and Text Analysis for Government
Summary and Conclusion for Government
Requirements
- Experience with Python programming for government applications
- General understanding of financial and banking principles relevant to public sector operations
- Basic knowledge of statistical and mathematical concepts used in governmental analysis
Testimonials (2)
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
Course - Natural Language Processing with TensorFlow
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
