Machine Learning
(Project based learning + Internship).

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Program Duration

4 weeks

Last Date to Apply

April 20, 2021

Program Starts

May 1, 2021

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    4 Weeks Online Class
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    4 Weeks Online Class
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    Machine Learning With Python

    Instructor
    Will be announced soon...

    Course Description

    Introduction:
    • Introduction to Data Science and Machine Learning
    • Examples & Techniques of Machine Learning
    • Real Life Industry Based ML Problem Statements
    Python:
    • Python Installation Guidelines
    • How to use Jupyter Notebook
    • Introduction to Python
    • Python programs
    • Python Data Structures-List
    • Python Data Structures-Dictionary
    • Python Data Structures-Sets
    • Python Data Structures-Strings
    • Python Data Structures-Tuples
    • Python Numpy
    • Python Pandas-Data Frames
    • Python Pandas-Series
    • Python Pandas-Quick-tips
    Statistics:
    • Basics of Statistics
    • Central Tendency
    • Covariance
    • Correlation
    • Standard Deviation
    • Z-Score
    Data Processing:
    • Data processing techniques in Python
    • Matplotlib Python visualization library
    • Box Plots
    • Histograms
    • Label Encoding
    • One Hot Encoding
    • Training and Testing data
    K-means
    • Introduction to Clustering
    • Understanding Income Group data set
    • Understanding of K-means Algorithm
    • Implementation of K-means in Python(Income Group)
    • Elbow Test Method
    Dimensionality Reduction:
    • Principal Component Analysis(PCA)
    • PCA implementation in Python
    Statistics: Feature Scaling:
    • Normalization
    • Standardization
    • Implementation of Feature scaling in Python
    Decision Tree:
    • Understanding of Decision Tree
    • Identification of Root Node
    • Implementation in Python
    Evaluation: Confusion Matrix:
    • Accuracy
    • Recall
    • Precision
    • F-Score
    Random Forest:
    • Understanding of Random Forest
    • Bagging Techniques
    • Implementation in Python
    K-Nearest Neighbours:
    • Understanding of KNN algorithm
    • Understanding of iris dataset
    • Implementation in Python
    Linear Regression:
    • Understanding of Linear Regression
    • Assumptions of Linear Regression
    • Implementation in Python
    • Problems in achieving accuracy of model
    • R-Square
    • Adjusted R-Square
    • Bias
    • Variance
    • Trade-Off between Bias and Variance
    Polynomial Regression:
    • Understanding of Polynomial Regression
    • Implementation in Python
    • Visualization of output by changing parameters
    Regularization Techniques
    • Ridge Regression
    • LASSO Regression
    • Elastic Net Regression
    Logistic Regression:
    • Understanding of Logistic Regression
    • Implementation in Python
    • Pros and Cons
    Naive Bayes:
    • Understanding of Naives Bayes
    • Examples
    • Pros and Cons
    • Implementation in Python
    Support Vector Machines:
    • Understanding of Support Vector Machines(SVM)
    • Understanding of different Scenarios
    • Pros and Cons
    • Implementation in Python
    Azure Cloud: Azure Machine Learning Studio:
    • Understanding of Azure ML Studio
    • Implementation of case study in Azure ML Studio Demo
    NLP Basics:
    • What are NLP and NLTK?
    • NLP setup and overview
    • Reading the text data
    • Exploring the dataset
    • What are Regular Expressions
    • Machine Learning Pipeline
    Implementation:
    • Removing Punctuation
    • Tokenization
    • Removing stop words
    Supplementing Data Cleaning:
    • Stemming
    • Lemmatizing
    • Text Summarizing-Word Cloud and Topic modelling
    Vectorizing Raw Data:
    • Count Vectorizing
    • N-gram Vectorizing
    • Inverse document frequency weighting

    Sentimental Analysis in Jupyter Notebook

    Preview of live class

    Real-Time Industry Applicable Projects

    These projects can be used as your Mini or Mojor Projects

    Image Recognition

    Develop a software to identify objects, people, places, and actions in images.

    Spam Detection

    Develop a Spam Filter from Scratch Using Machine Learning.

    Medical Diagnosis

    Develop a medical test system to detect infections, conditions and diseases.

    Social Media Sentiment Analysis

    Develop a social media analytics tool that involves checking how many negative and positive keywords are present in a chunk of conversation.

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    Frequently Asked Questions

    • This Program is offered by India's best Industry expert with minimum Experience of > 4 years.
    • It is an in-depth and comprehensive Program suitable for all aspirants.
    • Unique 4-step learning process: Masterclass Lectures, Hands-on , Mentor ship, and Workshops to ensure fast-track learning.
    • Led by collaborative Faculty from Academia, Industry and Global Blue chip Institutions.
    • Competitive and affordable pricing.

    Yes! This Program will help you in getting the Job, Last 2 days of the program is designed to connect you the Industry.

    • 64-bit Operating System
    • 2 GB RAM, 4 GB RAM Recommended

    Online is recommended as you don't need to travel.

    • Course Completion Certificate

    All the classes Online or Offline are recorded and will be shared on daily basis to every Students .