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Welcome to KGP Talkie's Natural Language Processing (NLP) course. It is designed to give you a complete understanding of Text Processing and Mining with the use of State-of-the-Art NLP algorithms in Python.
We will learn Spacy in detail and we will also explore the uses of NLP in real life. This course covers the basics of NLP to advance topics like word2vec, GloVe, Deep Learning for NLP like CNN, ANN, and LSTM. I will also show you how you can optimize your ML code by using various tools of sklean in python. At the end part of this course, you will learn how to generate poetry by using LSTM. Multi-Label and Multi-class classification is explained. At least 12 NLP Projects are covered in this course. You will learn various ways of solving edge-cutting NLP problems.
You should have an introductory knowledge of Python and Machine Learning before enrolling in this course.
In this course, we will start from level 0 to the advanced level.
We will start with basics like what is machine learning and how it works. Thereafter I will take you to Python, Numpy, and Pandas crash course. If you have prior experience you can skip these sections. The real game of NLP will start with Spacy Introduction where I will take you through various steps of NLP preprocessing. We will be using Spacy and NLTK mostly for the text data preprocessing.
In the next section, we will learn about working with files to store and load text data. This section is the foundation of another section on Complete Text Preprocessing. I will show you many ways of text preprocessing using Spacy and Regular Expressions. Finally, I will show you how you can create your own python package on preprocessing. It will help us to improve our code-writing skills. We will be able to reuse our code systemwide without writing codes for preprocessing every time. This section is the most important section.
Then, we will start the Machine learning theory section and a walkthrough of the Scikit-Learn Python package where we will learn how to write clean ML code. Thereafter, we will develop our first text classifier for SPAM and HAM message classification. I will also show you various types of word embeddings used in NLP like Bag of Words, Term Frequency, IDF, and TF-IDF. I will show you how you can estimate these features from scratch as well as with the help of the Scikit-Learn package.
Thereafter we will learn about the machine learning model deployment. We will also learn various other essential tools like word2vec, GloVe, Deep Learning, CNN, LSTM, RNN, etc.
Covered Keywords
Natural Language Processing, Python, Beginners, NLP, Text Processing, Text Analysis, Machine Learning, Data Science, Artificial Intelligence, Natural Language Understanding, Text Mining, Text Classification, Sentiment Analysis, Named Entity, Speech Recognition, Language Modeling, Text Generation, Text Summarization, Text Clustering, Text Similarity, Text Preprocessing, Regular Expressions, NLTK, spaCy, Gensim, Scikit-learn, TensorFlow, Keras, Numpy, Pandas, Jupyter Notebook, Data Visualization.
At the end of this lesson, you will learn everything which you need to solve your own NLP problem.
Everything You Need to Know About 2023 Natural Language Processing in Python for Beginners
This course is a comprehensive and well-structured introduction to 2023 Natural Language Processing in Python for Beginners. The instructor, Laxmi Kant | KGP Talkie, is a leading expert in the field with a wealth of experience in Development to share.
The course is well-structured and easy to follow, and the instructor does a great job of explaining complex concepts in a clear and concise way.
The course is divided into sections, each of which covers a different aspect related to Data Science. Each module contains a series of video lectures, readings, and hands-on exercises.
The instructor does a great job of explaining each topic in a clear and concise way. He/She also provides plenty of examples and exercises to help students learn the material.
One of the things I liked most about this course is that it is very practical. The instructor focuses on teaching students the skills and knowledge they need to succeed in the real world. He/She also provides students with access to a variety of resources, including templates, checklists, and cheat sheets.
Another thing I liked about this course is that it is offered on Udemy. Udemy is a great platform for taking online courses because it offers a lot of flexibility for students. Students can choose to take courses at their own pace, and they can access the course materials from anywhere with an internet connection.
Udemy also offers a variety of payment options, so students can find a plan that works for them. The course also has a very active community forum where students can ask questions and interact with each other. The instructor is also very responsive to student questions and feedback.
Overall, I highly recommend this course to anyone who is interested in learning 2023 Natural Language Processing in Python for Beginners. It is a well-organized and informative course that will teach you the skills and knowledge you need to succeed.
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