Artificial Intelligence course in Austin, US

CNN History
Understanding CNNs
CNN Application

Intro to RNN Model
Long Short-Term memory (LSTM)
Recursive Neural Tensor Network Theory
Recurrent Neural Network Model

Applications of Unsupervised Learning
Restricted Boltzmann Machine
Collaborative Filtering with RBM

Introduction to Autoencoders and Applications
Autoencoders
Deep Belief Network

Introduction to Anaconda
Installation of Anaconda Python Distribution : For Windows
Mac OS
and Linux
Jupyter Notebook Installation
Jupyter Notebook Introduction
Variable Assignment
Basic Data Types: Integer
Float
String
None and Boolean; Typecasting
Creating
Accessing
and slicing tuples
Creating
accessing
and slicing lists
Creating
viewing
accessing
and modifying dicts
Creating and using operations on sets
Basic Operators: 'in', '+', '*', Functions
Control Flow

NumPy Overview
Properties
Purpose
and Types of ndarray
Class and Attributes of ndarray Object
Basic Operations: Concept and Examples
Accessing Array Elements: Indexing
Slicing
Iteration
Indexing with Boolean Arrays
Copy and Views
Universal Functions (ufunc)
Shape Manipulation
Broadcasting
Linear Algebra

Introduction to Pandas
Data Structures
Series
DataFrame
Missing Values
Data Operations
Data Standardization
Pandas File Read and Write Support
Data Acquisition (Import & Export)
Selection
Filtering
Combining and Merging Data Frames
Normalization method
Removing Duplicates & String Manipulation

Introduction to Data Visualization
Python Libraries
Plots
Matplotlib Features
Line Properties Plot with (x, y)
Controlling Line Patterns and Colors
Set Axis
Labels
and Legend Properties
Alpha and Annotation
Multiple Plots
Subplots
Seabo

Neurons
ANN & Working
Single Layer Perceptron Model
Multilayer Neural Network
Feed Forward Neural Network
Cost Function Formation
Applying Gradient Descent Algorithm
Backpropagation Algorithm & Mathematical Modelling
Programming Flow for backpropagation algorithm
Use Cases of ANN
Programming SLNN using Python
Programming MLNN using Python
Digit Recognition using MLNN
XOR Logic using MLNN & Backpropagation
Diabetes Data Predictive Analysis using ANN

Hierarchical Clustering
K Means Clustering
Use Cases for K Means Clustering
Programming for K Means using Python
Image Color Quantization using K Means Clustering Technique
Clustering

Dimensionality Reduction
Data Compression
Concept and Mathematical modeling
Use Cases
Programming using Python
IRIS Data Analysis using PCA

Understand limitations of A Single Perceptron
Understand Neural Networks in Detail
Backpropagation : Learning Algorithm
Understand Backpropagation : Using Neural Network Example

Why Deep Learning?
SONAR Dataset Classification
What is Deep Learning?
Feature Extraction
Working of a Deep Network
Training using Backpropagation
Variants of Gradient Descent
Types of Deep Networks

Introduction to CNNs
CNNs Application
Architecture of a CNN
Convolution and Pooling layers in a CNN
Understanding and Visualizing a CNN
Transfer Learning and Fine-tuning Convolutional Neural Networks
Image classification using Keras deep learning library

Lists and Tuples
Sets
Dictionaries

Conditions and Branching
Loops
Functions
Objects and Classes

Reading files with open
Writing files with open
Loading data with Pandas
Working with and Saving data with Pandas

What is Data Science?
Data Science, Machine Learning, AI?
The Data-Related Roles
The Data Science Ecosystem
Tools of the Trade
Who is a Data Scientist?
Data Scientists at Work
Examples of Data Science Projects
An Example of a Data Product
Applied Data Science at Google
Data Science Gotchas

Typical Data Processing Pipeline
Data Discovery Phase
Data Harvesting Phase
Data Priming Phase
Exploratory Data Analysis
Model Planning Phase
Model Building Phase
Communicating the Results
Production Roll-out
Data Logistics and Data Governance
Data Processing Workflow Engines
Apache Airflow
Data Lineage and Provenance
Apache NiFi

Descriptive Statistics
Non-uniformity of a Probability Distribution
Using NumPy for Calculating Descriptive Statistics Measures
Finding Min and Max in NumPy
Using pandas for Calculating Descriptive Statistics Measures
Correlation
Regression and Correlation
Covariance
Getting Pairwise Correlation and Covariance Measures
Finding Min and Max in pandas DataFrame

Repairing and Normalizing Data
Dealing with the Missing Data
Sample Data Set
Getting Info on Null Data
Dropping a Column
Interpolating Missing Data in pandas
Replacing the Missing Values with the Mean Value
Scaling (Normalizing) the Data
Data Preprocessing with scikit-learn
Scaling with the scale() Function
The MinMaxScaler Object

Types of Machine Learning
Terminology: Features and Observations
Representing Observations
Terminology: Labels
Terminology: Continuous and Categorical Features
Continuous Features
Categorical Features
Common Distance Metrics
The Euclidean Distance
What is a Model
Supervised vs Unsupervised Machine Learning
Supervised Machine Learning Algorithms
Unsupervised Machine Learning Algorithms
Choosing the Right Algorithm
The scikit-learn Package
scikit-learn Estimators, Models, and Predictors
Model Evaluation
The Error Rate
Confusion Matrix
The Binary Classification Confusion Matrix
Multi-class Classification Confusion Matrix Example
ROC Curve
Example of an ROC Curve
The AUC Metric
Feature Engineering
Scaling of the Features
Feature Blending (Creating Synthetic Features)
The 'One-Hot' Encoding Scheme
Example of 'One-Hot' Encoding Scheme
Bias-Variance (UnderfittingvsOverfitting) Trade-off
The Modeling Error Factors
One Way to Visualize Bias and Variance
UnderfittingvsOverfitting Visualization
Balancing Off the Bias-Variance Ratio
Regularization in scikit-learn
Regularization, Take Two
Dimensionality Reduction
PCA and isomap
The Advantages of Dimensionality Reduction
The LIBSVM format
Life-cycles of Machine Learning Development
Data Splitting into Training and Test Datasets
ML Model Tuning Visually
Data Splitting in scikit-learn
Cross-Validation Technique
Hands-on Exercise
Classification (Supervised ML) Examples
Classifying with k-Nearest Neighbors
k-Nearest Neighbors Algorithm
Hands-on Exercise
Regression Analysis
Regression vs Correlation
Regression vs Classification
Simple Linear Regression Model
Linear Regression Illustration
Least-Squares Method (LSM)
Gradient Descent Optimization
Multiple Regression Analysis
Evaluating Regression Model Accuracy
The R2 Model Score
The MSE Model Score
Logistic Regression (Logit)
Interpreting Logistic Regression Results
Decision Trees and Terminology
Properties of Decision Trees
Decision Tree Classification in the Context of Information Theory
The Simplified Decision Tree Algorithm
Using Decision Trees
Random Forests
Hands-On Exercise
Support Vector Machines (SVMs)
Naive Bayes Classifier (SL)
Naive Bayesian Probabilistic Model in a Nutshell
Bayes Formula
Classification of Documents with Naive Bayes
Unsupervised Learning Type: Clustering
Clustering Examples
k-Means Clustering (UL)
k-Means Clustering in a Nutshell
k-Means Characteristics
Global vs Local Minimum Explained
Hands-On Exercise
XGBoost
Gradient Boosting
Hands-On Exercise
A Better Algorithm or More Data?

What is Python?
Additional Documentation
Which version of Python am I running?
Python Dev Tools and REPLs
IPython
Jupyter
Jupyter Operation Modes
Jupyter Common Commands
Anaconda
Python Variables and Basic Syntax
Variable Scopes
PEP8
The Python Programs
Getting Help
Variable Types
Assigning Multiple Values to Multiple Variables
Null (None)
Strings
Finding Index of a Substring
String Splitting
Triple-Delimited String Literals
Raw String Literals
String Formatting and Interpolation
Boolean and Boolean Operators
Numbers
Looking Up the Runtime Type of a Variable
Divisions
Assignment-with-Operation
Comments:
Relational Operators
The if-elif-else Triad
An if-elif-else Example
Conditional Expressions (a.k.a. Ternary Operator)
The While-Break-Continue Triad
The for Loop
try-except-finally
Lists
Main List Methods
Dictionaries
Working with Dictionaries
Sets
Common Set Operations
Set Operations Examples
Finding Unique Elements in a List
Enumerate
Tuples
Unpacking Tuples
Functions
Dealing with Arbitrary Number of Parameters
Keyword Function Parameters
The range Object
Random Numbers
Python Modules
Importing Modules
Installing Modules
Listing Methods in a Module
Creating Your Own Modules
Creating a Runnable Application
List Comprehension
Zipping Lists
Working with Files
Reading and Writing Files
Reading Command-Line Parameters
Accessing Environment Variables
What is Functional Programming (FP)?
Terminology: Higher-Order Functions
Lambda Functions in Python
Example: Lambdas in the Sorted Function
Other Examples of Using Lambdas
Regular Expressions
Using Regular Expressions Examples
Python Data Science-Centric Libraries