Python Bootcamp
- Category Other
- Type Tutorials
- Language English
- Total size 3.8 GB
- Uploaded By freecoursewb
- Downloads 478
- Last checked 1 day ago
- Date uploaded 3 months ago
- Seeders 11
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Infohash : 2D4AF3F86EB5F0C76C59FDDBFC6E00D90A23EB13
Python Bootcamp
https://WebToolTip.com
Published 9/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 9h 36m | Size: 3.78 GB
Master Python and unlock power of data with NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, TensorFlow, and PyTorch
What you'll learn
Gain a thorough understanding of Python syntax, script writing, and core concepts such as variables, data types, and string operations
Master the use of conditional statements and loops in Python to automate and optimize data processing tasks
Learn to design reusable Python functions to perform repetitive tasks efficiently, including recursion and lambda functions
Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance
Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format
Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python
Gain hands-on experience with Scikit-Learn, applying supervised and unsupervised learning algorithms to solve real-world machine learning problems
Understand the fundamentals of Deep Learning and neural networks, forming the foundation to work with TensorFlow and PyTorch frameworks
Build and evaluate deep learning models in PyTorch, including projects such as Fashion MNIST classification and cancer prediction
Requirements
No prior experience in Python or data analysis is required; just basic computer skills and access to a computer with an internet connection are necessary to start this course.
Files:
[ WebToolTip.com ] Python Bootcamp- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Introduction
- 1 -Introduction.mp4 (18.6 MB)
- 2 - Course resources.html (0.1 KB) Python Bootcamp files
- ML Intro PPT.pptx (8.9 MB)
- PyTorch_Tutorial.ipynb (13.2 KB) Python training data till Seaborn
- Housing.csv (29.3 KB)
- Housing.xlsx (37.5 KB)
- Housing_with_null.csv (29.1 KB)
- MatplotLib.ipynb (1,003.8 KB)
- Numpy.ipynb (53.1 KB)
- Pandas.ipynb (233.8 KB)
- Python_Tutorial.ipynb (139.8 KB)
- Seaborn.ipynb (2.0 MB)
- example.txt (0.0 KB)
- Scikit_Learn_Tutorial.ipynb (4.8 KB)
- deep learning intro.pptx (997.8 KB)
- tensorflow_Tutorial.ipynb (17.3 KB) 10 - Pandas Library
- 1 -Introduction to Pandas DataFrames.mp4 (40.8 MB)
- 2 -Working with Series and DataFrames.mp4 (47.3 MB)
- 3 -Core Methods for Data Analysis in Pandas.mp4 (111.6 MB)
- 4 -Handling Missing and Null Data.mp4 (109.2 MB)
- 5 -DataFrame Transformation and Manipulation.mp4 (110.6 MB)
- 1 -Getting Started with Matplotlib Library.mp4 (39.5 MB)
- 2 -Plotting Fundamentals Creating and Customizing Visuals.mp4 (116.5 MB)
- 3 -Subplots and Scatter Plots Comparative and Relational Analysis.mp4 (78.1 MB)
- 4 -Bar Charts, Histograms, and Pie Charts Distribution and Composition Insights.mp4 (85.8 MB)
- 1 -Introduction to the Seaborn Library.mp4 (71.5 MB)
- 2 -Visualizing Distributions Univariate and Bivariate Analysis.mp4 (50.4 MB)
- 3 -Advanced Plots in Seaborn Pairplots and Barplot Customization.mp4 (88.6 MB)
- 4 -Complex Visualizations Countplots and Heatmaps.mp4 (63.9 MB)
- 1 -Introduction to Scikit-Learn and Environment Setup.mp4 (43.3 MB)
- 2 -Data Loading Utilities in Scikit-Learn.mp4 (61.6 MB)
- 3 -Supervised Learning with Scikit-Learn.mp4 (46.3 MB)
- 4 -Unsupervised Learning with Scikit-Learn.mp4 (63.6 MB)
- 5 -Data Transformation Techniques in Scikit-Learn.mp4 (74.7 MB)
- 6 -Model Selection and Evaluation in Scikit-Learn.mp4 (77.3 MB)
- 7 -Visualization Tools in Scikit-Learn.mp4 (50.5 MB)
- 8 -Saving and Reusing Models in Scikit-Learn.mp4 (44.9 MB)
- 1 -Introduction to Deep Learning.mp4 (100.8 MB)
- 1 -Introduction to TensorFlow.mp4 (56.5 MB)
- 2 -Working with Tensors and TensorFlow Operations.mp4 (64.9 MB)
- 3 -Key Components of TensorFlow.mp4 (27.9 MB)
- 4 -Building Models with Keras in TensorFlow.mp4 (135.9 MB)
- 5 -Understanding the Variety of Layers in Neural Networks.mp4 (41.8 MB)
- 6 -Project – Fashion MNIST Classification with TensorFlow.mp4 (178.9 MB)
- 1 -Introduction to PyTorch.mp4 (65.9 MB)
- 2 -Tensor Operations in PyTorch.mp4 (49.9 MB)
- 3 -Building Neural Networks with PyTorch.mp4 (76.8 MB)
- 4 -Project – Melanoma Cancer Prediction with PyTorch.mp4 (49.6 MB)
- 5 -Project Extension – Data Augmentation for Cancer Prediction.mp4 (55.0 MB)
- 6 -Project Extension – Defining a Custom Neural Network.mp4 (96.9 MB)
- 7 -Evaluating Models with Confusion Matrix in PyTorch.mp4 (35.9 MB)
- 8 -The final milestone!.mp4 (12.7 MB)
- 1 - About your certificate.html (0.9 KB)
- 1 - Bonus Lecture.html (9.1 KB)
- 1 -What is Python & Why Learn It.mp4 (37.1 MB)
- 2 -This is a Milestone!.mp4 (43.7 MB)
- 3 -Understanding Variables in Python.mp4 (67.5 MB)
- 4 -Python Data Types.mp4 (38.9 MB)
- 5 -Working with Strings in Python.mp4 (48.2 MB)
- 6 -Useful String Methods.mp4 (82.5 MB)
- 1 -Lists in Python.mp4 (75.0 MB)
- 2 -Understanding Tuples.mp4 (41.6 MB)
- 3 -Working with Dictionaries.mp4 (36.8 MB)
- 4 -Sets in Python.mp4 (29.9 MB)
- 1 -Introduction to Conditional Statements.mp4 (31.7 MB)
- 2 -Operators and Advanced Conditions.mp4 (79.7 MB)
- 1 -For Loops in Python.mp4 (76.9 MB)
- 2 -While Loops in Python.mp4 (51.6 MB)
- 1 -Defining and Using Functions.mp4 (70.7 MB)
- 2 -Understanding Recursion.mp4 (52.6 MB)
- 3 -Lambda Functions in Python.mp4 (49.5 MB)
- 1 -Reading and Writing Files in Python.mp4 (69.4 MB)
- 1 -Introduction to Machine Learning.mp4 (100.8 MB)
- 1 -Overview of NumPy and Its Core Concepts.mp4 (60.8 MB)
- 2 -Indexing and Selecting Data in NumPy Arrays.mp4 (33.5 MB)
- 3 -Understanding Array Data Types, Shapes, and Stacking.mp4 (53.0 MB)
- 4 -Techniques for Creating Arrays in NumPy.mp4 (42.7 MB)
- 5 -Performing Mathematical and Statistical Operations with Arrays.mp4 (46.1 MB)
- Bonus Resources.txt (0.1 KB)
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