Python Machine Learning Course — Natural Language Processing (NLP) Using Python 2020
Python Machine Learning Training Course - Natural Language Processing (NLP) Using Python 2020, suitable for beginners and professionals who want to enhance their skills.
Syllabus
•Session 1 (1.5 hrs): Introduction to Python Machine Learning: history, uses, and industry scope
•Session 9 (1.5 hrs): Simple Case Study: Python Machine Learning Applications in the Workplace
•Session 10 (1.5 hrs): Review basic material & understanding quiz
Enroll in This Course
Python Machine Learning Course — Natural Language Processing (NLP) Using Python 2020
Machine Learning Course, Learn Natural Language Processing with Python, Machine Learning, Deep Learning, SpaCy, NLTK, Sklearn, CNN, RNN & much more!
What You Will Learn In This Machine Learning Course:
Complete Understanding of Natural Language Processing in this machine learning course
Implement NLP-related tasks with Scikit-learn, NLTK and SpaCy
Apply Machine Learning Models to Classify Text Data
Text Classification (Spam Detection, Amazon Product Review Classification)
Text Summarization (Convert 5000 word articles into 200 Words)
Calculate Sentiment Score from Recent Tweets (Twitter API)
Refresh Your Deep Learning Concepts (ANN, CNN & RNN)
Build Your Own Word Embedding Model (Word2vec) with Keras
Applications of Word Embeddings with Google Pretrained Model
Spam Message Detection with CNN and RNN Based Neural Networks
Automatic Text Generation using TensorFlow, Keras and LSTM
Working with Text & PDF Files in Python (PyPDF2 module)
Tokenization, Stemming, and Lemmatization
Stop Words, Parts of Speech (POS) Tagging with NLTK
Vocabulary, Matching, Named Entity Recognition (NER)
Data Analysis with Numpy and Pandas
Data Visualization with libraries
Prerequisites
Basic understanding of Python Programming
Machine Learning Course Description:
Do you have an idea about which field of Artificial Intelligence will be big in the coming years?
According to statista dot com which AI field is projected to reach $43 billion by 2025?
If your answer is 'Natural Language Processing', you are in the right place.
How Google News classifies millions of news articles into hundreds of different categories.
How Android voice recognition recognizes your voice with high accuracy.
How Google Translate actually translates hundreds of different language pairs into one another.
If your answer is "Yes", you are on the right track.
Frequently Asked Questions
Is this Python Machine Learning course suitable for beginners?▾
The material is structured in stages starting from basic concepts, so participants without prior experience can still follow along with instructor guidance.
What is the learning method?▾
Live online classes via Zoom with experienced instructors, hands-on practice, and recorded sessions that can be replayed. There is also an in-house training option for companies.
Is there a final project that can be used as a portfolio?▾
Yes, each participant completes an end-to-end mini project that can be directly used as a portfolio or thesis/dissertation material.
Do I get a certificate after completion?▾
Yes, participants who complete the program receive an official e-certificate from Cerdas Inovasi Digital.
How do I register?▾
Click the registration button on this course page or contact our admin for schedule consultation and packages that suit your needs.
NLP – "Natural Language Processing" has found its place in every aspect of our daily life.
Mobile phone internet is an integral part of our life. In every application most of the time you will find the use of NLP methods, from Google search engine to Amazon & Netflix recommendation systems.
Chatbots
Google Now, Apple Siri, Amazon Alexa
Machine Translation
Sentiment Analysis
Speech Recognition and much more.
So, welcome to my course on NLP.
Complete Natural Language Processing (NLP) with Spacy & NLTK
Learning Scheme:
1: Welcome In this Machine Learning course section we will get a complete idea of what we will learn throughout the entire course and understanding related to natural language processing.
2: Installation & Setup In this section we will get the online setup of Google Colab.
3: Fundamentals of Natural Language Processing In this section we will cover all basic NLP tasks such as Tokenization, Lemmatization, stop word removal, named entity recognition, parts of speech tagging, and see how to implement with various functions available in Spacy and NLTK libraries.
4, 5, 6: Spam Message Classification, Restaurant Review Prediction (Good or Bad), IMDB, Amazon and Yelp Review Classification
In the next 3 sections we will dive into real-world datasets for text classification, spam detection, restaurant review classification, Amazon IMDb reviews. We will see how to perform Pre-Processing and make your data suitable for machine learning algorithms and apply different Machine Learning estimators (Logistic Regression, SVM, Decision Tree) to classify text.
7, 8: Automatic Text Summarization, Twitter Sentiment Analysis In these 2 sections we will discuss real-world NLP applications.
Automatic text summarization, which compresses your text to find summaries of large articles
Another one we will work on is finding the sentiment of recently posted tweets about some specific keywords with the help of Twitter API – tweepy library
9: Fundamentals of Deep Learning In this section we will get a basic idea about deep learning concepts, such as activation functions of artificial neural networks and how ANNs work.
10: Word Embeddings In this section, we will see how to implement word2vec on our specific dataset, as well as use Pretrained Google Model.
11, 12: Text Classification with CNN & RNN In this section we will see how to apply deep learning models such as convolutional neural networks and recurrent neural networks for text classification.
13: Automatic Text Generation using TensorFlow, Keras and LSTM In this section we will apply LSTM-based neural network model to automatically generate text.
14, 15, 16, 17: Numpy, Pandas, Matplotlib + File Processing In this section, for those of you who want to refresh concepts related to data analysis with Numpy and Pandas libraries, Data Visualization with Matplotlib libraries, and Text and PDF File Processing.
So, this is one of the most comprehensive courses on natural language processing,
And I expect you to have basic knowledge of python and your curiosity to learn various techniques in the world of NLP.
Who This Course Is For:
Anyone interested in learning Natural Language Processing
Learning Methods at Cerdas Inovasi Digital
Live online classes via Zoom with experienced instructors, hands-on practice with real case studies, and session recordings that can be played back. In-house training packages are also available for corporate needs throughout Indonesia.
Contact us for consultation on schedules and packages that best suit your needs.
