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Machine Learning Training

Machine Learning Training - Analytics ath

Course Detail

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Course Description

Key Highlights of Our Training Program:

 

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    6 experts faculty team from IIT & IIM alumina

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    Curriculum with wide coverage and practical assignments

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    Excellent lab facility with 24*7 expert support

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    Flexible weekday and weekend class timings

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    100% guaranteed placement assistance

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    Get recognized by top hiring companies

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    Free workshop sessions on demand

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    Affordable course fee

Workshop Dates

 

FREE WORKSHOP

  • Date : 12th December,2021
  • Time : 10:00 am to 11:30 am
  • Mode : Classroom
Register For Free

NEW REGULAR BATCH

  • Date : 8th December,2021
  • Time : 7:00 am to 9:00 am
  • Mode : Classroom
Register Now

NEW WEEKEND BATCH

  • Date : 11th December,2021
  • Time : 9:00 am to 3:30 pm
  • Mode : Classroom
Register Now

Path To Become a Machine Learning

 

Course Curriculum

 

Python For Data Science:

  • Python Programming Introduction
  • Data Types and Data Structures
  • Control Statements
  • Functions
  • User Defined Functions
  • Python Packages
  • Numpy, Pandas. Matplotlib

Machine Learning In Python:

  • Scikit-Learn
  • Use Cases And Assignments

R-Programming

  • R and R-Studio installation
  • Data types and Data structures
  • Arithmetic, logical operations
  • Conditional statements
  • Loops
  • Packages and functions in R
  • Data Frame operations
  • Getting data into R from flat files
  • Connecting to databases
  • Data Inspection and Manipulation Data wrangling and data munging

Big Data Analytics

  • Hadoop Architecture, HDFS
  • MapReduce
  • Hive, Hbase, Sqoop
  • Spark Architecture, Spark Core
  • Spark Sql, Spark Mllib

Machine Learning With Spark

  • Spark Context and Hive Context
  • Dataframes, Datasets in Spark
  • Scala Introduction
  • Pyspark
  • Machine Learning Use Cases on Spark

Introduction To Data Science

  • Probability refresher
  • Descriptive Statistic
  • Measures of central tendency
  • Measures of spread
  • Distribution
  • Different types of distributions: Normal, Binomial, and Poisson
  • Probability Density functions
  • Characteristics of normal distribution
  • Sampling distribution
  • Inferential Statistics
  • Hypothesis testing (t-test, chi-square )
  • Analysis of variance
  • Measures of relationship: Correlation, covariance , associations and odds ratio

Exploratory Data Analysis and Visualization

  • Summary Statistics
  • Data Distributions
  • Outlier Detection and Management
  • Charts and Graphs
  • One Dimensional
  • Charts Histogram • Barchart
  • Two Dimensional
  • Scatter Plots • Box Plots • Bar Charts (Stack And Dodge)
  • Multi-Dimensional Plots
  • Inference and Variable Selection
  • Fancy Charts-Bubble Charts, Word Clouds

Data Pre-processing

  • Data Types and Conversion
  • Binning and Normalization
  • Scaling
  • Imputation

Artificial Intelligence

  • Text Mining
  • Deep Learning
  • ANN
  • CNN (Computer Vision)
  • RNN/LSTM

Deep Learning

Deep Learning Frameworks

  • Tensorflow
  • Keras

Artificial Neural Networks (ANN)

  • Perceptron
  • Activation Functions
  • Single Layer Perceptron
  • Forward & Backward Propagation
  • Gradient Descent Optimization
  • Batch • Stochastic • Mini-batch
  • Training & Epochs
  • Multilayered Perceptron
  • Dropout & Dropconnect

Convolutional Neural Networks (CNN)

  • CNN For Computer Vision
  • Convolution Operation
  • Filters & Feature Maps
  • Pooling Operation
  • Deep CNN
  • Padding & Strides
  • Training of CNN

Recurrent Neural Networks (RNN)

  • Sequential Networks
  • RNN Structures
  • BPTT Process
  • Varnishing & Exploding Gradients
  • LSTM
  • Word Embedding
  • •Glove •Word2Vec

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Institute Overview

Analytics ath
Hyderabad, Telangana, India
4 Current Posted Courses

Analytics Path is a pionner institute that offers training in the trending data analytical technologies like Data Science, Artificial Intelligence, Machine Learning, Deep Learning, & TensorFlow. Backed by a team of expert trainers, we help our st... Read More

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