- Overview of Text Mining
- Need of Text Mining
- Natural Language Processing (NLP) in Text Mining
- Applications of Text Mining
- OS Module
- Reading, Writing to text and word files
- Setting the NLTK Environment
- Accessing the NLTK Corpora
Online
5 Weeks
₹ 19,995
Quick facts
particular | details | ||
---|---|---|---|
Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
|
Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekends
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Course overview
Edureka's natural language processing with python guides a candidate step by step to nlp and text analytics using python's programming language. Anyone working with text and data and little knowledge of python programming language can take up this course. However, they provide a complimentary course to brush up skills on python programming.
Nlp is a form of artificial intelligence which has a great significance on the way humans and computers interact. This course has a lot of practical situations where candidates can apply what they have learnt. Topics such as text processing, semantics analysis, machine learning and other such topics have been discussed.
Their syllabus is designed in such a manner that they take a candidate through all the important concepts which are required while applying the learning of nlp. It discusses real life problems, and after this course one can build their own machine learning model for text classification.
The highlights
- Instructor led sessions
- Assignments
- Real life case studies
- Lifetime access
- 24x7 expert support
- Certification from Edureka
- Learning forum
Program offerings
- Online classes
- Assignments
Course and certificate fees
Fees information
Edureka's NLP Certification Training with Python course. details are given below:
- Fees of Rs. 19,995/- are to be paid for pursuing this course.
- However, they have a triple bonanza offer where you can get a flat 10 percent off plus 20 percent cashback plus a free self-paced course.
Heads | Amount (in INR) |
Course Fee | 19,995/- |
EMI | 6,665 / month |
certificate availability
certificate providing authority
Eligibility criteria
Education
Candidates taking up this course should know a little about python programming and should have a good understanding of the concept of machine learning. However, they have a complementary course on python offered by edureka.
Certification qualifying details
Candidates will be given a certificate of completion only after clearing all the projects and submitting the tests. On completion of the programme, the candidates will be awarded with certification of completion.
What you will learn
After completing this course successfully one will be able to :
- Build your own text classifier
- Know processes such as text processing, semantic analysis, machine learning.
- Work on nltk corpora
- analyse sentence structure
- Extract, clean and pre process text
- Handle real time data efficiently
- Know deeply about role played by a 'nlp' engineer
- Master the art of step by step text processing using i python notebooks
- Gain expertise to handle business in future , living in the present
- Use n-gram models to model and analyze the bag of words from corpus
- Learn about latent semantic analysis and its usage in the processing of context aware semantic content
- Learn about bag of words modelling and tokenization of text
- Learn techniques to access or modify some of the most common file types
- Learn basics of nlp in the most popular python library : nltk
- Learn about converting text to vectors using word frequency count, tf-idf etc.
Who it is for
Edureka's NLP Certification Training with Python course is recommended for :
- Developers aspiring to be a ‘data scientist'
- A college student having exposure to programming to a technical architect/lead in an organisation
- Analytics managers who are leading a team of analysts
- 'Python' professionals who want to design automatic predictive models on text data
- Business analysts who want to understand text mining techniques
- It is open for everyone
Admission details
The Edureka's NLP Certification Training with Python course. Admission procedure is very simple.
Candidates may follow the given steps to register themselves-
Step 1: Open the website by clicking on the URL : https://www.edureka.co/python-natural-language-processing-course.
Step 2: Click on the 'sign up' option given on the rightmost corner and create a new account.
Step 3: enter your email and phone number and proceed further.
Step 4: save this email for future use.
Or
Step 1: click on the 'enroll now' option.
Step 2: enter your email id and mobile number.
Step 3: click on 'begin now'.
Step 4: start your learning.
The syllabus
Introduction to Text Mining and NLP
Topics
Hands-On/Demo
- Install NLTK Packages using NLTK Downloader
- Accessing your operating system using the OS Module in Python
- How to read json format, understand key-value pairs, and for that matter, understand uses of pkl files
Extracting, Cleaning and Pre-processing Text
Topics
- Tokenization
- Frequency Distribution
- Different Types of Tokenizers
- Bigrams, Trigrams & Ngrams
- Stemming
- Lemmatization
- Stopwords
- POS Tagging
- Named Entity Recognition
Hands-On/Demo
- Regex, Word, Blankline, Sentence Tokenizers
- Bigrams, Trigrams & Ngrams
- Stopword Removal
- UTF encoding, dealing with URLs, hashtags
- POS Tagging
- Named Entity Recognition (NER)
Analyzing Sentence Structure
Topics
- Syntax Trees
- Chunking
- Chinking
- Context Free Grammars (CFG)
- Automating Text Paraphrasing
Hands-On/Demo
- Parsing Syntax Trees
- Chunking
- Chinking
- Automate Text Paraphrasing using CFG’s
Text Classification - I
Topics
- Machine Learning: Brush Up
- Bag of Words
- Count Vectorizer
- Term Frequency (TF)
- Inverse Document Frequency (IDF)
Hands-On/Demo
- Demonstrate Bag of Words Approach
- Working with CountVectorizer()
- Using TF & IDF
Introduction to Deep Learning
Topics
- What is Deep Learning?
- Curse of Dimensionality
- Machine Learning vs. Deep Learning
- Use cases of Deep Learning
- Human Brain vs. Neural Network
- What is Perceptron?
- Learning Rate
- Epoch
- Batch Size
- Activation Function
- Single Layer Perceptron
Hands-On/Demo
- Single Layer Perceptron
Getting Started with TensorFlow 2.0
Topics
- Introduction to TensorFlow 2.x
- Installing TensorFlow 2.x
- Defining Sequence model layers
- Activation Function
- Layer Types
- Model Compilation
- Model Optimizer
- Model Loss Function
- Model Training
- Digit Classification using Simple Neural Network in TensorFlow 2.x
- Improving the model
- Adding Hidden Layer
- Adding Dropout
- Using Adam Optimizer
Hands-On
- Classifying handwritten digits using TensorFlow 2.0
Convolution Neural Network
Topics
- Image Classification Example
- What is Convolution
- Convolutional Layer Network
- Convolutional Layer
- Filtering
- ReLU Layer
- Pooling
- Data Flattening
- Fully Connected Layer
- Predicting a cat or a dog
- Saving and Loading a Model
- Face Detection using OpenCV
Hands-On
- Saving and Loading a Model
- Face Detection using OpenCV
Regional CNN
Topics
- Regional-CNN
- Selective Search Algorithm
- Bounding Box Regression
- SVM in RCNN
- Pre-trained Model
- Model Accuracy
- Model Inference Time
- Model Size Comparison
- Transfer Learning
- Object Detection – Evaluation
- mAP
- IoU
- RCNN – Speed Bottleneck
- Fast R-CNN
- RoI Pooling
- Fast R-CNN – Speed Bottleneck
- Faster R-CNN
- Feature Pyramid Network (FPN)
- Regional Proposal Network (RPN)
- Mask R-CNN
Hands-on/Demo
- Transfer Learning
- Object Detection
Boltzmann Machine & Autoencoder
Topics
- What is Boltzmann Machine (BM)?
- Identify the issues with BM
- Why did RBM come into the picture?
- Step-by-step implementation of RBM
- Distribution of Boltzmann Machine
- Understanding Autoencoders
- Architecture of Autoencoders
- Brief on types of Autoencoders
- Applications of Autoencoders
Hands-on/Demo
- Implement RBM
- Simple encoder
Generative Adversarial Network(GAN)
Topics
- Which Face is Fake?
- Understanding GAN
- What is Generative Adversarial Network?
- How does GAN work?
- Step by step Generative Adversarial Network implementation
- Types of GAN
- Recent Advances: GAN
Hands-on/Demo
- Implement Generative Adversarial Network
Emotion and Gender Detection (Self-paced)
Topics
- Where do we use Emotion and Gender Detection?
- How does it work?
- Emotion Detection architecture
- Face/Emotion detection using Haar Cascade
- Implementation on Colab
Hands-on/Demo
- Implement Emotion and Gender Detection
Introduction to RNN and GRU (Self-paced)
Topics
- Issues with Feed Forward Network
- Recurrent Neural Network (RNN)
- Architecture of RNN
- Calculation in RNN
- Backpropagation and Loss calculation
- Applications of RNN
- Vanishing Gradient
- Exploding Gradient
- What is GRU?
- Components of GRU
- Update gate
- Reset gate
- Current memory content
- Final memory at current time step
Hands-on/Demo
- Implement COVID RNN GRU
LSTM (Self-paced)
How it helps
NLP is one form of artificial intelligence which has a great scope in future. This course help machines and humans interact with each other. If one wants to go in this field of artificial intelligence, then edureka's NLP Certification Training with Python course is very essential as it provides exactly what an employer wants and what one should know before stepping into this field.
Candidates who have successfully completed this course are placed in companies like dell, vmware, honeywell, cisco and many others. The certificate will shower ample employment opportunities on candidates. It will yield a higher package. Mean salary of a person with this course is $128,857.
NLP is bridging the gap between humans and machines and this is going to be the future. It opens job opportunities in international spheres. It is a highly developing concept and the desires for the professionals with this certificate are constantly increasing. It is a time friendly course which will be conducted in batches as per your convenience.
This course is a boon for the CV of a professional and will highlight it. The real life projects provided by it help you to analyze the real life problems which will be beneficial in future also.
FAQs
The assignment given by them shall have real life problems where you can apply your knowledge gained by this certificate course.
There is no problem if a candidate misses a session. One can view recorded sessions available in lms and also one can attend the sessions in another live session.
They have a 24x7 support system where one can clear doubts anytime.
If your problems are not solved in the support system you can contact them at +91 90660 20867/1844 230 6362 (us toll free number) or email at sales@edureka.co.
Candidates with certificates of this course are placed in companies like Dell, Honeywell, cisco, Vmware.
After signing up the access to study material is given instantly. Access to pre recorded videos and other material made available by them is also given.
The access of this course is available lifetime once you enroll in this course.
This course can be taken up by anyone. They provide a complementary course to polish your knowledge on python programming.