NATURAL LANGUAGE PROCESSINGNLP USING ML DLTF IN PYTHON
Python Certification Course
Lateral Entry Professionals and Freshers
Online and Offline Classes
Week Days and Week Ends
Daily 2 hrs during Weekdays
•Learn to build apps with Python.
•What are the advantages of Python?
•Learn to code with Python the easy way.
•Different Python practical questions asked during real time interviews .
•Learn Python from Scratch with Demos and Practical examples.
•Learn fundamentals of Python for Beginners: Practical and hands-on learning
•This course will teach you how to get moving in Python.
•Feel more confident in handling real life scenarios and writing complex codes
•Learn how to code in Python This Python Course is set up for complete beginners!
•Real-world skills + project portfolio
•We Groom up your documents and profiles
•Get Certified at the Best Training Institute.
•We enage Experienced trainers for Quality Training
•Facility of Lab on cloud available (based on booking)
•Project manager can be assigned to track candidates’ performance
•One-on-one training, online training, team or Corporate training can be provided
•This Instructor-led classroom course is designed with an aim to build theoretical knowledge supplemented by ample hands-on lab exercises
•Asp.net Mvc Developer, Asp.net Mvc Lead, Java Developer(spring), Ui Developer, Ui Lead, Data Architect
•Java Programmer, Ui Designer, Web Developer, Web Designer, Automation Testing, graphic designer visualiser, java script frameworks, PHP
•Protocol Testing, Php Developer, Oracle, Senior Managers, Oracle DBA, Dotnet, Java, oracle, DBA, Database Administration, 12c, RAC, Goldengate
•Webmethods, Spot Fire, Tableau, Sap, Dwh, Oracle Apps, Oracle Dba, Calypso, Murex, Ui Developer, Core Java, Peoplesoft, Jd Edwards, Dot Net, Liferay, C++
Introduction and Walk through of contents
•Presentation ppt and Python code
•Installations and Technology
•What Is Natural Language Processing
•Applications of NLP
•Basic string operations
•NLTK Install and Testing
•NLTK Part-of-speech tagging
•NLTK Stemming and Lemmatization
•NLTK Word-sense disambiguation
•NLTK BLEU Scores
•String Cleaning part1
•String Cleaning part2
•String Cleaning part3
•String Cleaning part4
•Overall approach for NLP solutions
•Entity resolution or Deduplication
•Entity resolution or Deduplication – data prep
•Entity resolution or Deduplication – single table
•Entity resolution or Deduplication – two tables
•Text to Features – One hot encoding
•TF-IDF (Term Frequency, Inverse Document Frequency)
•Word2vec and GloVe
•Word embedding of custom review data
•Word Sense Disambiguation
•Speech Recognition using Microphone
•Speech Recognition using Audio Files
•Similarity between two strings
•Computational Linguistics – Dependency Extraction
•Advance – Introductions
•Classifications using Random Forest
•Classifications using Naive Bayes and XgBoost
•Classifications using DL with tfkeras MLP
•Classifications using DL with tfkeras inbuilt embedded layer
•Classifications using DL with tfkeras WordVector transformed to average
•Classifications using DL with tfkeras custom WordVector
•How to know models are good enough Bias vs Variance