Facebook Instagram Linkedin Telegram

Ammerpet, Hyderabad

Address

Monday - Friday 6am - 8pm

Timeing

info@arjunanalytics.com

Mail to us

Facebook Instagram Linkedin Telegram
  • Ammerpet, Hyderabad
  • +91 9912622633
  • info@arjunanalytics.com
Register Now

Machine learning

SUPERVISED LEARNING

UNSUPERVISED LEARNING

CLASSIFICATION

  • Logistic Regression
  • Decision Tree
  • SVC – SVC
  • Naïve Bayes
  • KNN
  • Ensemble
  • Random Forest
  • Ada Boost
  • Gradient Boost
  • XG Boos

REGRESSION

  • Linear
  • Regression Multi
  • Linear Reg
  • Polynomial Reg
  • Ridge Regression
  • Decision Tree
  • SVM — SVR
  • Ensemble Methods

CLUSTERING

  • K-Means
  • C-Means
  • Hierarchical
  • Neural Network

MACHINE LEARNING

(MODULE – 3)

Linear Regression

CLASSIFICATION

  • What is Correlation
  • What is Regression
  • What is Linear Regression
  • Linear Regression
  • Overview Simple Linear
  • Regression Multi Linear
  • Regression Polynomial
  • Regression Related Concepts
  • Bias
  • Variance
  • Bias-Variance 
  • Under Fitting Problem
  • Over Fitting Problem

REGRESSION

  • What is Regularization
  • Types of Regularization
  • Lasso Regression
  • Ridge Regression
  • Mathematical Intuition
  • Linear Regression
  • Polynomial Regression
  • Lasso Regression
  • Ridge Regression

Regression / Evolution Metrics  

  • What is Actual Value
  • What is Predicted Value
  • What is Residual
  • R Squared (R^2)
  • Mean Squared Error (MSE)
  • Root Mean Squared Error (RMSE)
  • Mean Absolute Error (MAE)

CLUSTERING & TIME SERIES

(MODULE – 3)

CLUSTERING

  • What is Clustering
  • Types of Clustering Methods 
  • Partitioning Clustering
  • Hierarchical Clustering 
  • Density Based Clustering 
  • K-Means Clustering algorithm   
  • Implement K-Means
  • Hierarchical Clustering Algorithm
  • Implement Hierarchical Clustering

TIME SERIES ANALYSIS

  • Time Series data ?
  • Format Time Series data
  • components of Time Series data
  • Time Series scenarios
  • Time Series Model Selection
  • Time Series Model for Forecast
  • What is ARIMA Model ?
  • Implementation of ARIMA model

IMAGE PROCESSING USING OPENCV

  • Image to Numpy
  • Array Grayscale
  • Image
  • Image Resize
  • Image Events
  • Image Flip
  • Image crop

ENSEMBLE LEARNING

(MODULE – 3)

ENSEMBLE LEARNING

  • Introduction to Ensemble Learning
  • Weak Learning?
  • Types of Ensemble Learning
  • Bagging
  • Boosting
  • What is Bagging Mechanism
  • Random Forest
  • Implementation of RF
  • What is Boosting Mechanism
  • Boosting Algorithms
  • Ada Boost
  • Gradient Boost
  • XG Boost
  • Implementation of
  • Ada Boost
  • Gradient Boost
  • XG Boost

HYPERPARAMETER TUNING

  • What is Hyperparameter?
  • Types of Hyperparameter
  • Tuning Grid Search Tuning
  • Randomize Search Tuning

CROSS VALIDATION

  • What is Cross Validation?
  • Why we need Cross Validation
  • Types of Cross Validation
  • Leave One Out Cross Validation
  • Hold Out Cross Validation Method
  • K-Fold Cross Validation Method
  • Stratified Cross Validation Method

DEEP LEARNING

(MODULE – 4)

DEEP LEARNING

  • What is Deep Learning
  • Machine Learning VS Deep Learning
  •  Biological Neural Network
  • Deep Learning Application
  • Artificial Neural Network (ANN)
  • Convolutional Neural Network (CNN)
  • Recurrent Neural Network(RNN)

TENSOR FLOW

  • What is TensorFlow
  •  What are Tensors
  • Tensor Graph
  • TensorFlow Perceptron
  •  Single Layer Perceptron
  •  Hidden Layer Perceptron
  •  Multi-Layer Perceptron

ACTIVATION FUNCTION

  • What is Activation Function
  • Types of Activation Function
  •  Relu
  •  Leaky Relu

ACTIVATION FUNCTION

  • Tan
  • Sigmoid
  •  Softmax
  • What is Optimizer
  • What is Loss Function

KERAS

  • What is Keras
  •  Keras Model
  • Sequential Model
  •  Functional Model
  •  Keras Layers
  •  Input Layer
  •  Output Layer
  •  Dense Layer
  •  Flatten Layer
  • Convolutional Layer
  • Pooling Layer
  •  Recurrent Layer
  • Embedding Layer

DEEP LEARNING

(MODULE – 4)

ARTIFICIAL NEURAL NETWORK

  • The Detailed ANN 
  •  How do ANNs work
  • Gradient Descent
  •  Stochastic Gradient Descent
  •  Forward Propagation
  •  Back propagation
  •  limitations of a Single Perceptron
  •  Neural Networks in Detail
  •  Understand Backpropagation

NATURAL LANGUAGE PROCESSING

  • Natural Language Processing?
  • Types of Hyperparameter
  • Tokenization
  • Stemming
  • Lemmatization
  • Stop Words
  • Phrase Matching
  • Vocabulary
  • Part of Speech Tagging
  • Named Entity Recognition
  • Part of Speech Tagging
  • Named Entity Recognition
  • Sentence Segmentation
  • Sentiment Analysis with NLTK
  • Text Classification
  • Recurrent Neural Network
  • LSTM
  • RNN Layers
  • Network Layer
  • Embedded Layer

COMPUTER VISION (Using CNN)

  • What is ComputerVision
  • Convolutional Neural Network
  •  Why CNN
  • Application on CNN
  •  Convolutional Layers
  • Pooling Layers
  • Batch Normalization Layers
  •  Dropout Layers

ADDITIONAL CONCEPTS

(MODULE – 5)

HADOOP

  • Hadoop Introduction
  • Hadoop Architecture
  • Hadoop Eco – System
  • HDFS
  • Hadoop Coursera
  • Py-Spark
  • Hive

KAFKA

  • What is Message Service
  • Kafka Introduction
  • Kafka Architecture
  • Implementation with Python

FLASK

  • Flask Introduction
  • Flask Application
  • Flask URL
  • Templates
  • Merge the ML Model

AGILE SCRUM METHODOLOGY

  • Agile Introduction
  • Advantages of Agile
  • Scrum Introduction
  •  Scrum Process
  • Scrum Terminology

AMAZON WEB SERVICES

  • Cloud Computing
  • AWS
  • Introduction
  • Creating AWS Account
  • EC2 Details
  • Deploying Flask & ML Model

©2024. K.M.A ARJUN ANALYTICS . All Rights Reserved.