Natural Language Processing Real-World Projects in Python
- Description
- Curriculum
- FAQ
- Reviews
Are you looking to land a top-paying job in Data Science , AI & Natural Language Processing?
Or are you a seasoned AI practitioner who want to take your career to the next level?
Or are you an aspiring data scientist who wants to get Hands-on Data Science and Artificial Intelligence?
If the answer is yes to any of these questions, then this course is for you!
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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3
Datasets & Resources -
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Introduction to Business Problem & Dataset -
5
Perform Data Pre-processing on Amazon Data
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6
Apply Exploratory Data Analysis on Data
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7
Intuition behind Bag of Words
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8
Intuition behind Logistic Regression --part 1
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9
Intuition behind Logistic Regression --part 2
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10
Apply Bag of Words on data
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11
Automate your NLP model & Machine Learning Model
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12
Intuition behind TF-IDF --part 1
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13
Intuition behind TF-IDF --part 2
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14
Applying algorithms of NLP & Machine Learning
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15
Data Preparation for Modelling Purpose
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16
Applying Techniques of Handling Imbalance Data & Cross Validation
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17
Datasets & Resources
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18
Introduction to Business Problem & Dataset
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19
Data Pre-processing on Data.
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20
Perfrom Data Wrangling & Merging
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21
Intuition Behind Random Forest Part-1
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22
Intuition behind Random Forest --part 2
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23
Apply Bag of words and Random forest on Data
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24
Model Evaluation..
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25
Intuition Behind Naive Bayes-Part 1
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26
Intuition Behind Naive Bayes- Part 2
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27
Apply Naive Bayes on Data..
