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24-12-2020, 15:00

Data Science with ML, AI, GUI & VUI with Libraries of Python

Category: Tutorials » Other
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 122 lectures (16h 23m) | Size: 6.46 GB

Data Science, Machine Learning , Artificial Intelligence, Graphical User Interface, Speech Recognition with Python
What you'll learn:
The course provides path to start career in Data Science , Artificial Intelligence, Machine Learning, Graphical User Interface and Speech Recognition
Problem Solving Approach
Impress interviewers by showing an understanding of the recent industrial trends
Learn Python Basic to Advance Concept with Numpy, Pandas, MatDescriptionlib, Seaborn, Descriptionly Library
Scikit Learn Library in Depth
Machine Learning Algorithms such as Linear, Logistic, SVM, KNN, K Mean, Naïve Bayes, Decision Tree and Random Forest
Machine Learning Types Such as Supervise Learning, Unsupervised Learning, Reinforcement Learning
Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation
Case Study of Robotics (Unmanned Ground Vehicle)
Speech Recognition
Understand how you can create your own styles and use them in your applications
Learn wide variety of widgets, such as Button,Canvas ,Checkbutton, Entry, Label, Listbox, Menubutton, Message, Radiobutton, Scrollbar, Toplevel, Spinbox, PanedWindow, LabelFrame
Project on GUI and VUI such as Text to Speech, Digital Clock, Today's Day using Speech Recognition, Restart your Computer with Speech Recognition, Convert image to text and text to speech
It start with Basics
Only a passion for Learning
All software used in this course is either available for Free or as a Demo version
This course is intended for absolute beginners in programming
This Course all in one. it covered topics such as
1. Python Basic Concepts, Python Advance Concepts,
2. Numpy Library , Scipy Library , Pandas Library,
3. MatDescriptionlib Library, Seaborn Library, Descriptionlypy Library.
4. The Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered with case studies using Scikit Learn library.
5. Machine Learning Types such as Supervise Learning, Unsupervised Learning, Reinforcement Learning are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.
6. Case Study on Artificial Intelligence (AI) for Unmanned Ground Vehicle (UGV)
7. CLI (Command Line Interface), GUI (Graphical User Interface) and VUI (Voice User Interface), Tkinter Library Use for GUI Development, Speech Recognition, Voice User Interface (VUI), Text to Speech, Speech to Text, Project of GUI and VUI
Who this course is for
The course is ideal for beginners, as it starts from the fundamentals and gradually builds up your skills in Machine Learning Algorithms, AI, Data Science, GUI, Speech Recognition, Python

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