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Udemy - Applied Text Mining and Sentiment Analysis with Python

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961.03 MB

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2470bac3d740eba4ecd833d965f28ec0b0ca1c17

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24-02-2021 15:42

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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/1. Course Preview/1. Preview.mp4	69.96 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/1. Course Preview/1. Preview.srt	5.22 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/1. Section Overview.mp4	29.04 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/1. Section Overview.srt	1.95 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/10. (Python Practice) Dataset Visualization.mp4	22.18 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/10. (Python Practice) Dataset Visualization.srt	3.66 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/10.1 Colab_Notebook_Section_1_completed.ipynb	78.55 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/2. What is Text.mp4	20.48 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/2. What is Text.srt	3.47 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/2.1 Section 1 - Theory Deck.pdf	2.58 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/3. What is Text Mining.mp4	19.04 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/3. What is Text Mining.srt	3.10 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/4. Text Mining and NLP.mp4	14.61 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/4. Text Mining and NLP.srt	2.41 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/5. Sentiment Analysis.mp4	16.29 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/5. Sentiment Analysis.srt	2.74 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/6. Roadmap.mp4	16.19 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/7. (Python Practice) Google Colab.mp4	12.35 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/7. (Python Practice) Google Colab.srt	3.15 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/7.1 Colab_Notebook.ipynb	77.50 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/8. (Python Practice) Dataset Connection.mp4	21.24 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/8. (Python Practice) Dataset Connection.srt	3.79 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/8.1 tweet_data.csv	1.75 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/9. (Python Practice) Dataset Overview.mp4	16.21 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/2. Introduction to Text Mining/9. (Python Practice) Dataset Overview.srt	2.99 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/1. Section Overview.mp4	18.57 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/10. (Python Practice) Applied Tokenization (33).mp4	18.30 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/11. Stemming.mp4	18.08 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/13. Lemmatization.mp4	14.77 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/14. (Python Practice) Applied Lemmatization.mp4	18.65 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/14. (Python Practice) Applied Lemmatization.srt	3.87 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/15. (Python Pratice) Tweet Pre-Processing.mp4	8.37 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/2. What is Text Normalization.mp4	19.55 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/2. What is Text Normalization.srt	3.73 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/2.1 Section 2 - Theory Deck.pdf	1.80 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/3. Text Cleaning (12) - Twitter Features.mp4	22.18 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/3. Text Cleaning (12) - Twitter Features.srt	4.20 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/4. (Python Practice) Cleaning Twitter Features.mp4	38.05 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/4. (Python Practice) Cleaning Twitter Features.srt	7.98 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/5. Text Cleaning (22) - General Features.mp4	18.73 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/6. (Python Practice) Cleaning General Features.mp4	30.82 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/6. (Python Practice) Cleaning General Features.srt	6.56 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/7. Tokenization.mp4	26.19 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/3. Text Normalization/8. (Python Practice) Applied Tokenization (13).mp4	12.59 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/1. Section Overview.mp4	22.52 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/2. Why Representing Text.mp4	17.61 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/2.1 Section 3 - Theory Deck.pdf	1.53 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/3. PositiveNegative Word Frequencies.mp4	23.26 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/4. (Python Practice) Applied PositiveNegative Frequencies.mp4	20.96 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/5. Bag-of-Words.mp4	19.60 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/6. (Python Practice) Applied Bag-of-Words.mp4	29.08 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/6. (Python Practice) Applied Bag-of-Words.srt	5.77 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/7. TF-IDF.mp4	23.45 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/8. (Python Practice) Applied TF-IDF.mp4	17.68 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/4. Text Vectorization/8.1 Colab_Notebook_Section_3_completed.ipynb	83.75 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/1. Section Overview.mp4	17.20 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/2. Why a model.mp4	11.69 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/2.1 Section 4 - Theory Deck.pdf	1.57 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/3. Logistic Regression.mp4	37.45 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/4. ML Model Training.mp4	33.84 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/5. (Python Practice) TrainTest split.mp4	16.89 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/6. (Python Practice) ML Model Fitting.mp4	29.49 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/7. Model Performance Measures.mp4	33.47 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/8. (Python Practice) Applied Performance Measures.mp4	19.11 MB
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[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/8.1 Colab_Notebook_Section_4_completed.ipynb	85.30 kB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/9. (Python Practice) Prediction Pipeline.mp4	12.63 MB
[TutsNode.com] - Applied Text Mining and Sentiment Analysis with Python/5. Sentiment Analysis/9. (Python Practice) Prediction Pipeline.srt	2.12 kB

Description

Description

“Bitcoin (BTC) price just reached a new ALL TIME HIGH! #cryptocurrency #bitcoin #bullish”

For you and me, it seems pretty obvious that this is good news about Bitcoin, isn’t it? But is it that easy for a machine to understand it? … Probably not … Well, this is exactly what this course is about: learning how to build a Machine Learning model capable of reading and classifying all this news for us!

Since 2006, Twitter has been a continuously growing source of information, keeping us informed about all and nothing. It is estimated that more than 6,000 tweets are exchanged on the platform every second, making it an inexhaustible mine of information that it would be a shame not to use.

Fortunately, there are different ways to process tweets in an automated way, and retrieve precise information in an instant … Interested in learning such a solution in a quick and easy way? Take a look below …

_____________________________________________________

What will you learn in this course?

By taking this course, you will learn all the steps necessary to build your own Tweet Sentiment prediction model. That said, you will learn much more as the course is separated into 4 different parts, linked together, but providing its share of knowledge in a particular field (Text Mining, NLP and Machine Learning).

SECTION 1: Introduction to Text Mining

In this first section, we will go through several general elements setting up the starting problem and the different challenges to overcome with text data. This is also the section in which we will discover our Twitter dataset, using libraries such as Pandas and Matplotlib.

SECTION 2: Text Normalization

Twitter data are known to be very messy. This section will aim to clean up all our tweets in depth, using Text Mining techniques and some suitable libraries like NLTK. Tokenization, stemming or lemmatization will have no secret for you once you are done with this section.

SECTION 3: Text Representation

Before our cleansed data can be fed to our model, we will need to learn how to represent it the right way. This section will aim to cover different methods specific to this purpose and often used in NLP (Bag-of-Words, TF-IDF, etc.). This will give us an additional opportunity to use NLTK.

SECTION 4: ML Modelling

Finally … the most exciting step of all! This section will be about putting together all that we have learned, in order to build our Sentiment prediction model. Above all, it will be about having an opportunity to use one of the most used libraries in Machine Learning: Scikit-Learn (SKLEARN).

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Why is this course different from the others I can find on the same subject?

One of the key differentiators of this course is that it’s not about learning Text Mining, NLP or Machine Learning in general. The objective is to pursue a very precise goal (Sentiment Analysis) and deepen all the necessary steps in order to reach this goal, by using the appropriate tools.

So no, you might not yet be an unbeatable expert in Artificial Intelligence at the end of this course, sorry … but you will know exactly how, and why, your Sentiment application works so well.

_____________________________________________________

About AIOutsider

AIOutsider was created in 2020 with the ambition of facilitating the learning of Artificial Intelligence. Too often, the field has been seen as very opaque or requiring advanced knowledge in order to be used. At AIOutsider, we want to show that this is not the case. And while there are more difficult topics to cover, there are also topics that everyone can reach, just like the one presented in this course. If you want more, don’t hesitate to visit our website!

_____________________________________________________

So, if you are interested in learning AI and how it can be used in real life to solve practical issues like Sentiment Analysis, there is only one thing left for you to do … learn with us and join this course!
Who this course is for:

Anyone having an interest in Artificial Intelligence and NLP
Anyone willing to learn what is Text Mining and how it can be used
Anyone willing to learn how to easily predict the sentiment of any tweet

Requirements

A basic Python IDE (Spyder, Pycharm, etc.) or a web-based Python IDE (Jupyter Notebook, Google Colab, etc.). Google Colab will be used by default to teach this course.
General knowledge of Python, as this is a course about learning Sentiment Analysis and Text Mining, not properly about learning Python.

Last Updated 2/2021