| 1 - Introduction.mp4 | 9.7 MB | ||
| 10 - Assigning Values.mp4 | 21.1 MB | ||
| 11 - Value Membership Deleting and Filtering.mp4 | 15.6 MB | ||
| 12 - Nested Dict and Transposition.mp4 | 23.5 MB | ||
| 13 - Methods and Duplicate Labels.mp4 | 28.9 MB | ||
| 14 - Reindexing.mp4 | 34.3 MB | ||
| 15 - Dropping.mp4 | 21.9 MB | ||
| 16 - Arithmetic and Data Alignment.mp4 | 33.3 MB | ||
| 17 - Arithmetic Methods.mp4 | 10.1 MB | ||
| 18 - DataFrame and Series and Operations.mp4 | 19.4 MB | ||
| 19 - Functions by Element and Row or Column and Statistics.mp4 | 42.3 MB | ||
| 2 - Welcome to the Series.mp4 | 22 MB | ||
| 20 - Ranking and Sorting.mp4 | 40.5 MB | ||
| 21 - Covariance and Correlation.mp4 | 57.3 MB | ||
| 22 - Assigning a NaN Value.mp4 | 13 MB | ||
| 23 - NaN Value Filtration.mp4 | 27.3 MB | ||
| 24 - Filling.mp4 | 9.1 MB | ||
| 25 - Hierarchical Indexing.mp4 | 48.6 MB | ||
| 3 - Internal Elements and Assigning Values.mp4 | 11.2 MB | ||
| 4 - Defining Series and Filtering Values.mp4 | 12.8 MB | ||
| 5 - Mathematical Functions and Evaluating Values.mp4 | 22.3 MB | ||
| 6 - NaN Values.mp4 | 13.4 MB | ||
| 7 - Dictionaries and Operations between Series.mp4 | 23.2 MB | ||
| 8 - DataFrame.mp4 | 47.8 MB | ||
| 9 - Selecting Elements.mp4 | 24.5 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 27 total files | |||
Deep Dive Into Mastering Data Science And Machine Learning
https://DevCourseWeb.com
Published 8/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 632.95 MB | Duration: 2h 0m
Unleash Data's Power: Analyze, Predict, Transform - Data Science, ML Algorithms, Model Deployment, Visualization
What you'll learn
Proficiently preprocess and clean diverse datasets for analysis.
Apply a wide array of machine learning algorithms to solve various tasks.
Expertly perform feature engineering to enhance model performance.
Visualize data effectively to extract insights and communicate findings.
Deploy machine learning models using cloud services and containers.
Evaluate model performance and fine-tune hyperparameters for optimization.
Interpret and explain complex machine learning model predictions.
Work on end-to-end data science projects mirroring real-world scenarios.
Utilize ensemble methods and deep learning techniques for improved results.
Contribute to transparent and ethical data-driven decision-making processes.
Requirements
Nothing!
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 439.6 MB | freecoursewb | 1 month | 0 | 0 | |
| 392.9 MB | freecoursewb | 1 month | 0 | 2 | |
| 401.5 MB | freecoursewb | 3 months | 2 | 2 | |
| 2.5 GB | freecoursewb | 5 months | 0 | 0 | |
| 300.2 MB | freecoursewb | 5 months | 0 | 0 |
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