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TORRENT DETAILS
Udemy - Advance Python Python For Datascience
TORRENT SUMMARY
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The course is designed to provide students with a strong foundation in advanced Python programming, data analysis, and machine learning.
Students will learn advanced programming concepts, including list comprehensions, file I/O operations, exception handling, and lot more advance python concepts.
Data manipulation and analysis using the NumPy and Pandas libraries, covering data cleaning, preprocessing, and transformation techniques.
Data visualization using Matplotlib, Seaborn, and Plotly for creating informative and visually appealing plots and charts.
Implementation and evaluation of various machine learning algorithms, such as supervised and unsupervised learning, using the Scikit-learn library.
Optional exploration of advanced topics like natural language processing, web scraping, time series analysis, and recommender systems for a more comprehensive u
Requirements
Students should have understanding of fundamental Python concepts, including variables, data types, loops, and functions.
A genuine interest in working with data, conducting data analysis, and implementing machine learning models is crucial to fully benefit from the course content.
A foundational knowledge of basic mathematical concepts, such as algebra and statistics, will be helpful for comprehending certain aspects of data analysis, machine learning, and numerical computing.
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FILE LIST
Filename
Size
~Get Your Files Here !/1. Introduction to Python/1. Introduction to python (part-1).mp4
158.1 MB
~Get Your Files Here !/1. Introduction to Python/2. Introduction to python (part-2).mp4
154.1 MB
~Get Your Files Here !/2. Advanced Python Concepts/1. List Comprehension and Generators.mp4
179.2 MB
~Get Your Files Here !/2. Advanced Python Concepts/2. File Handling.mp4
138.6 MB
~Get Your Files Here !/2. Advanced Python Concepts/3. Exception handling.mp4
93.7 MB
~Get Your Files Here !/2. Advanced Python Concepts/4. Object Oriented Programming (oops).mp4
166.8 MB
~Get Your Files Here !/2. Advanced Python Concepts/5. Decorators and Metaclasses.mp4
96.5 MB
~Get Your Files Here !/3. NumPy (expand on the basic library coverage)/1. Arrays and Arrays Operations.mp4
206.2 MB
~Get Your Files Here !/3. NumPy (expand on the basic library coverage)/2. Array Indexing and Slicing.mp4
191.5 MB
~Get Your Files Here !/3. NumPy (expand on the basic library coverage)/3. Broadcasting and Vectorization.mp4
172.9 MB
~Get Your Files Here !/3. NumPy (expand on the basic library coverage)/4. Mathematical functions and Linalg.mp4
146.1 MB
~Get Your Files Here !/3. NumPy (expand on the basic library coverage)/5. Array Manipulation and Reshaping.mp4
126.6 MB
~Get Your Files Here !/4. Pandas (expand on the basic library coverage)/1. Pandas Datastructure.mp4
179.8 MB
~Get Your Files Here !/4. Pandas (expand on the basic library coverage)/2. Data Transformation and Manipulation.mp4
199.5 MB
~Get Your Files Here !/4. Pandas (expand on the basic library coverage)/3. Data Cleaning and Preprocessing.mp4
237.9 MB
~Get Your Files Here !/4. Pandas (expand on the basic library coverage)/4. Joining Merging and Reshaping.mp4
207 MB
~Get Your Files Here !/5. Data Visualization/1. Advanced Matplolib Techniques.mp4
206.6 MB
~Get Your Files Here !/5. Data Visualization/2. Seaborn.mp4
146.6 MB
~Get Your Files Here !/5. Data Visualization/3. Plotly.mp4
189 MB
~Get Your Files Here !/5. Data Visualization/4. Geospatial_Data_Analysis.mp4
226.9 MB
~Get Your Files Here !/6. Supervised Learning Algorithms/1. Linear Regression.mp4
216.1 MB
~Get Your Files Here !/6. Supervised Learning Algorithms/2. Logistic Regression.mp4
127.6 MB
~Get Your Files Here !/6. Supervised Learning Algorithms/3. Support Vector Machines, Decision Trees, Random Forests,.mp4
159.4 MB
~Get Your Files Here !/7. Unsupervised Learning Algorithms/1. 24. Unsupervised Learning.mp4
