Artificial Intelligence

NumPy
Pandas
MatPlot
Seaborn
Exploratory Data Analysis and Visualization
SciKit Learn
TensorFlow and Keras

Python Basics
Python List
Logic and flow control
Sequence List and Tuples
Files and Exception
Object Oriented Approach using Python
Regular Expression
Function and Packages
API development using Python

NumPy
Pandas
MatPlot
Seaborn
Exploratory Data Analysis and Visualization
SciKit Learn
TensorFlow and Keras

Matrices and vectors
Addition and scalar Multiplication
Mean, Standard Deviation, Median
Matrix vector multiplication
Matrix Multiplication and Properties
Inverse and Transpose
Coordinate systems
Mathematical Representation of a line (2D), plane(3D) and hyperplane (n*D)
Hyper planes and Hyper spaces
Geometric Representation of a circle (2D), sphere (3D) and hypersphere (n*D)
Equation of an ellipse (2D), ellipsoid (3D) and hyper ellipsoid (n*D)
Vector Spaces
Determinants
Eigen Vectors
Correlation, Coefficient intuition
Length and Dot Products
Linear Equations

Introduction to probability
Frequentist Interpretation
Bayesian Interpretation & Bayes Rules and Bayes Theorem
Analyze Dataset for Distributions
Refining the Qualitative and Quantitative Data.
Variation in Datasets (Univariate, Bivariate and Multivariate Data)
Population & Sample.
Gaussian/Normal Distribution and its PDF (Probability Density Function).
CDF (Cumulative Density Function) of Gaussian/Normal Distribution
Symmetric distribution, Skewness, and Kurtosis
Standard normal variate (z) and standardization.
Kernel density estimation.
Hypothesis Testing
Law of large Number?
Joint and Disjoint Outcomes
Probability Distribution
Sample Space and Complements
Probability Casting
Permutation and combination
Markov Decision Process
Discrete Sample Space (Finite and Infinite)
Events, Independence
Joint Probability and Conditional Probability
General Multiplication Rule
Inverting Probabilities
Z Score
Laws of Total Probability
Correlation and causation
Chebyshev’s inequality
Discrete and Continuous Uniform distributions.
Bernoulli and Binomial distribution

Transforming Biological neuron to Artificial Neurons
Logical Computations with Neurons
Single Layer Perceptron
Sequential Modelling
Multi-Layer Perceptron
Activation Functions
Loss functions
Vanishing/Exploding Gradients Problems
Batch Normalization
Learning Rates
Train Test and Validation
Overfitting and Underfitting Problems
Dealing with Data Augmentation.
One Hot Encoding
Dropout
Gradient Clipping

Intuition
Zero Padding
Convolution Layers
Max Pooling
Back Propagation
Weights and its Importance
Classification MLPs
Backpropagation
Dealing with Augmented Data
Reusing Pretrained Layers
Transfer Learning with Keras
Unsupervised Pretraining
Faster Optimizers
Momentum Optimization
Batch Size
Max-Norm Regularization
Fine Tuning
CNN Architectures
Self-Organizing Maps
Boltzmann Mechanism
Autoencoders

Intuition
RNN
Bidirectional RNN’S
LSTM
Memory Requirements

Discussion on LeNet-5
Discussion on AlexNet
Discussion on GoogLeNet
Discussion on VGGNet
Discussion on ResNet
Using Pretrained Models from Keras
Pretrained Models for Transfer Learning
Classification and Localization
Object Detection
Fully Convolutional Networks (FCNs)
You Only Look Once (YOLO)
Time Series Analysis
Generative Adversarial Network
Deploying Deep Learning Models using Django

TensorFlow and Keras Initation
Tensors and Operations
Tensors with NumPy
Placeholders
Type Conversions
Variables
Data Structures Indepth
TensorFlow Functions and Graphs
Building an Image Classifier
Using Sequential API to build Regression MLP
Using Sequential API to build Complex Models
Using the Sub classing API Saving and Restoring a Model
Implementing Callbacks
Visualization Using Tensor Board
Fine-Tuning Neural Network Hyperparameters
Hidden Layers
Learning Rate, Batch Size and Other Hyperparameters
Customizing Metrics, Layers, Training Loops , Models and Training Algorithms
Custom Loss Functions
Autograph and Tracing
TF Function Rules

Feature Engineering and Model Selection
Underfitting and overfitting
Bias, Variance Trade-off / F1scores
Confusion matrix
Accuracy metrics
Univariate, Bivariate, Multivariate Dataset
Evaluating machine learning model
ROC Curves
Hyper parameter tuning
Importance of Data and its quality
Attributes Types
Feature selection and Feature extraction
Stepwise Selection
Loss Function
Curse of Dimensionality
ChiSquare Test
Impact on Outliers
Cohen’s D Statistics
Error Analysis
General Distance metrics
Graph analysis on Datasets
Regularization
MSE, RMSE, MSE
Feature Slicing
Correlation and Causation
Training /Validation /Testing Data
Learning Rate
Confidence Intervals
Degree of Freedom
Coefficients and Collinearity
P value

1. PCA
2. LDA
3. QDA
Intuition on Dimensionality Reduction
Geometrical intuition.
Alternative formulation of PCA: distance minimization
Eigenvalues and eigenvectors.
PCA for dimensionality reduction and visualization.
Visualize MNIST dataset.
Limitations of PCA
Ts-SNE Estimator for Dimensionality Reduction
Impact on Algorithm

Holdout Method
K-Fold Cross Validation
Stratified K-Fold Cross Validation
Leave-One-Out Cross Validation

What is a web framework?
MVT design pattern
Importance of Django framework
Creating and running a Django project
Creating multiple applications
Defining URL patterns inside an application

Creating a template based application
Defining template tags
Application to display employee information
Inserting static files
Developing a blog application using static files

Configuring the database with sqlite3
Configuring the database with mysql
Configuring the database with mongodb
Importance make migrations and migrate
Creating a Bank database
Creating a Student database Module -4: Django Forms
Difference between HTML forms and Django forms
Form handling process
Form fields and validation
Model Forms
Implementing custom validators
Template inheritance and template filters
Creating a course registration form
Creating an employee information form

Session management with cookies
Permanent and temporary cookies
Django session framework
Important session methods
Deleting a session
Developing an online purchase application
Developing customer details management application

Creating views at class level
Creating a template file for ListView
Developing an online movie booking application
Developing an employee profile application
Developing a customer database application

Setting up of Django Rest framework
Rest Framework views
Creating custom action
PUT,POST,PATCH,DELETE methods
Working with Serializers classes
JWT Authentication
Handling relationships
Consuming third party API