Data Science

It's good for learning how to process text data and apply them to machine learning.

I like the real world workflow of getting and processing data before using machine learning.

Appreciated the machine learning review section too.

I am from a Linguistics background yet I understand everything explained Its Good This was not a tutorial just a rush follow along with video Explanation is very good and the design / order of content is excellent It was a great experiencing having to dive deeper into the Natural Language Preprocessing in Machine Learning.

Ideally, it could have more real word applications and some practical advices and details about when and how to implement machine learning algorithms.

May be more interesting by introducing 1 or 2 more challenging NLP problems or topics (NLU, NLG, etc...) If I have a little experience of machine learning, it's more through its application to computer vision.

Good course, not very basic, but still basic... you need some understand about Machine Learning.

Good for a complete begginer who has just heard about NLP/Machine learning and basic python understanding.

The machine learning review was so useful.

The course is a good introduction, with a basic Machine Learning knowledge it was quite simple.

Covers a nice amount of topics in NLP and machine learning.

Simple application of machine learning including classification, eigendecomposition and markov modeling.

Lazy programmer does a superb job of engaging the student throughout the course.

Thanks to the lazy programmer for putting the efforts in to make this course.

Lazy Programmer very clearly explains each model and the pros and cons of each one.

I am thankful to the Lazy Programmer for designing a course that introduces NLP to the beginner.

Lazy programmer is a superb teacher and explains each concept in simple ways for everyone to understand.

Lazy Programmer is really unique and presents the topic in a very appealing way.

I've taken a number of the Lazy Programmer's courses and enjoy his laid back style and presentation.

Looking forward to take other courses on deep learning so that i complete all prerequisite before taking Advance NLP by Lazy Programmer.

Lazy programmer is a great instructor and is able to convey the concepts in an intuitive way.

Lazy Programmer is a great instructor with great experience in the best way to learn the subject.

As always, the Lazy Programmer does not disappoint.

Thanks to lazy programmer for showing us simple applications of NLP.

Codes are short and easy to follow.

Code is easy to follow and modify for personal application.

Very easy to follow and code along to get a practical sense of how everything is working.

This is a good first course on NLP with easy to follow and straightforward examples.

The instructor explains things step-by-step so it's easy to follow.

Yes it seems good for beginning concise and well documented This course gives a pretty good overview of NLP Good start for newbies Easy to follow and merges and advanced concepts Useful course projects with hands on experience The course explains why and how clearly Excellent for base concepts in NLP in python.

liked what i have seen so far Practical examples that are easy to follow Not much theory, not much content or coding examples being considered More explanations needed and less watching code being typed.

This was a good introduction to natural language processing.

Content was solid and covered practical applications of natural language processing in Python.

Simple and to the point course on natural language processing.

Was expecting more Natural Language Processing, this seemed more about the next stage which was applying Machine Learning concepts to the already processed data.

Compelling and perfect introduction to the domain of natural language processing Good content and explanation.

Course was a good overview of natural language processing.

I found the sentiment analysis example was great.

The sentiment analysis exercise shows how to interpret the results of training the model.

The point of the section 11 "How to improve your sentiment analysis" is not to introduce RNN, but show how student are stupid.

It is great, you will learn sentiment analysis and advanced text transformation model.

In sentiment analysis he can include unsupervised learning like obtain negative, positive percent as well rather than just considering as text classification problem.

Very useful and true to the curriculum it teaches some NLP applications - spam detection, sentiment analysis, article spinning, ... After intense learning and excellent instruction, I get a little sense of machine learning now.

The spam detection exercise shows it is easy to do nlp in a plug and play manner.

The first example on spam detection was very simply plugging a dataset into scitkits.

You get a lot of practical exercises like spam detection article spinning.

For example the coverage of spam detection consisted only of training an existing sample model, with no discussion of either how to develop the model or how to use it in practice to actually do spam detection.

Direct and to the point examples like sentiment analysis and article spinning.

fantastic course, learned so much from the article spinning practical Fantastic course!

I would highly recommend this course.

I would totally recommend this course.

Would definiately recommend this course to professionals in the data science space The course was well organized and the instructor was very well prepared.

Less knowledge sharing I like the gradual intro good so far For the moment, not that interesting a good introduction to NLP Great course, thank You!

till now it is good so far so good good so far Looks very interesting!

Followable Very Good good so far Great introduction it is good gpood excellent very slow ok best 良い .

Course felt shallow, only few coding examples / applications (3, not counting latent semantic analysis) were discussed, in total includes only 3 hours of lectures.

The latent semantic exercise had interesting results too, when you could see the science and arts split on different areas of the chart.

The latent semantic analysis section shows how to use exploratory data analysis with nlp.

the sentiment analysis example was extremely helpful as was the the latent semantic analysis example.

You will have the opportunity to do spam detection, latent semantic analysis, NLTK, and article spinning.

It's great to have many practice attempts with real life data.

It helps a lot to do exercises which are connected to real life activities.

Well taught and applicable to real life.

simple explanations with real life tips and helpful exercises Description overstates what the course covers.

Encouraging to learn NLP rather than scaring people away with math excellent teaching by giving real life examples Nice course I like it!

The one about the article spinner was particularly fun and interesting Slow to begin/build up, a bit general but to be expected for an intro course.

The article spinner results are pretty funny, but it's understandable since this course isn't on deep learning, which might be required to get an improvement.

The chapter on article spinner need more explanation Fun course for someone who is new to NLP and is familiar with some basic machine learning and coding.

:) Lazy programmer does a fantastic job of explaining complex concepts in simple terms Not very detailed neither in the code part or the theory Every section teaches you tons of new coding techniques, I am excited now to build my own article spinner!