| 001 Intro To course.mp4 | 19.3 MB | ||
| 001 Introduction to Business Problem & Dataset.mp4 | 13.7 MB | ||
| 002 Datasets & Resources.html | 1.1 KB | ||
| 002 How to follow this course-Must Watch.mp4 | 17.2 MB | ||
| 003 Data Pre-processing on Data.mp4 | 84 MB | ||
| 003 Exploring Data.mp4 | 57.1 MB | ||
| 003 Perform Data Pre-processing on Amazon Data.mp4 | 60.2 MB | ||
| 004 Apply Exploratory Data Analysis on Data.mp4 | 51.9 MB | ||
| 004 Apply TF-IDF on data.mp4 | 60.5 MB | ||
| 004 Perfrom Data Wrangling & Merging.mp4 | 72 MB | ||
| 005 Apply Logistic Regression on Data.mp4 | 53 MB | ||
| 005 Intuition Behind Random Forest Part-1.mp4 | 77.8 MB | ||
| 005 Intuition behind Bag of Words.mp4 | 62.6 MB | ||
| 006 Checking Accuracy of Model.mp4 | 28.2 MB | ||
| 006 Intuition behind Logistic Regression --part 1.mp4 | 58 MB | ||
| 006 Intuition behind Random Forest --part 2.mp4 | 50.8 MB | ||
| 007 Apply Bag of words and Random forest on Data.mp4 | 62.2 MB | ||
| 007 Intuition behind Logistic Regression --part 2.mp4 | 44.1 MB | ||
| 008 Apply Bag of Words on data.mp4 | 96 MB | ||
| 008 Model Evaluation.mp4 | 50 MB | ||
| 009 Automate your NLP model & Machine Learning Model.mp4 | 107.1 MB | ||
| 009 Intuition Behind Naive Bayes-Part 1.mp4 | 69 MB | ||
| 010 Intuition Behind Naive Bayes- Part 2.mp4 | 92.6 MB | ||
| 010 Intuition behind TF-IDF --part 1.mp4 | 24.8 MB | ||
| 011 Apply Naive Bayes on Data.mp4 | 36.8 MB | ||
| 011 Intuition behind TF-IDF --part 2.mp4 | 34.6 MB | ||
| 012 Applying algorithms of NLP & Machine Learning.mp4 | 58.8 MB | ||
| 013 Data Preparation for Modelling Purpose.mp4 | 55.6 MB | ||
| 014 What is Imbalance Data & how to handle it__.mp4 | 85.5 MB | ||
| 015 Part1-- What is Cross-validation & when to use it__.mp4 | 41.7 MB | ||
| 016 Part2-- What is Cross-validation & when to use it__.mp4 | 67.3 MB | ||
| 017 Applying Techniques of Handling Imbalance Data & Cross Validation.mp4 | 99.3 MB | ||
| Downloaded from 1337x.html | 512 B | ||
| ▲ 37 total files | |||
Knowledge should not be limited to those who can afford it or those willing to pay for it.
If you found this course useful and are financially stable please consider supporting the creators by buying the course :)
Natural Language Processing Real-World Projects in Python
Solve 3 real Business Problems. Build Robust AI, NLP models for Sentiment, Security & Stock News Domain..
This course includes:
* 5.5 hours on-demand video
What you'll learn
* Hands on Real-World Projects on Various Domains of Natural Language Processing
* Develop Natural Language Processing Models to Customer Sentiments
* Develop Natural Language Processing Models to predict Stock News
* Develop Natural Language Processing Models to Predict the Strength of password
Data Science is one of the hottest tech fields to be in right now! The field is exploding with opportunities and career prospects. Data Science is widely adopted in many sectors nowadays such as banking, healthcare, Airlines, Logistic and technology.
In business, Data Science is applied to optimize business processes, maximize revenue and reduce cost. The purpose of this course is to provide you with knowledge of key aspects of data science applications in business in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets.
1.Task #1 @Predict Customer Sentiments : Develop an AI model to predict Customer Sentiments of Amazon..
3.Task #2 @Predict future Stock Prices: Develop NLP models to predict future Stock prices.
2.Task #3 @Predict the strength of a Password: Predict the category of Password whether it is Strong, Good or Weak.
Why should you take this Course?
It explains Projects on real Data and real-world Problems. No toy data! This is the simplest & best way to become a Data Scientist/AI Engineer/ ML Engineer/NLP Engineer
It shows and explains the full real-world Data. Starting with importing messy data, cleaning data, merging and concatenating data, grouping and aggregating data, Exploratory Data Analysis through to preparing and processing data for Statistics, Machine Learning , NLP & Time Series and Data Presentation.
In real-world projects, coding and the business side of things are equally important. This is probably the only course that teaches both: in-depth Python Coding and Big-Picture Thinking like How you can come up with a conclusion
Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.
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