Coursera Python Data Products for Predictive Analytics Specialization

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Download Free Download : Coursera Python Data Products for Predictive Analytics Specialization
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:1.5 GB
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Files Included :

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02 course-materials Final Course1.zip (631.29 KB)
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01 what-is-a-data-product.mp4 (11.62 MB)
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02 data-product-examples-in-enterprise.mp4 (12.46 MB)
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03 developing-a-data-product-strategy.mp4 (15.76 MB)
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01 python-and-jupyter-basics.mp4 (13.63 MB)
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02 python-recap.mp4 (10.78 MB)
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05 livecoding-getting-started-with-jupyter.mp4 (16.67 MB)
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01 csv-json-files.mp4 (18.24 MB)
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02 reading-csv-json-files.mp4 (17.38 MB)
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03 processing-structured-data-in-python.mp4 (16.08 MB)
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04 live-coding-json.mp4 (8.44 MB)
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01 extracting-simple-statistics-from-datasets.mp4 (20.71 MB)
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02 simple-statistics-live-coding.mp4 (12.97 MB)
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01 data-filtering-and-cleaning.mp4 (19.53 MB)
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01 processing-text-and-strings-in-python.mp4 (16.32 MB)
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02 processing-times-and-dates-in-python.mp4 (22.89 MB)
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03 livecoding-time-and-date-data.mp4 (12.7 MB)
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01 matrix-processing-and-numpy.mp4 (11 MB)
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01 introduction-to-data-visualization.mp4 (23.58 MB)
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02 introduction-to-matplotlib.mp4 (9.93 MB)
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03 live-coding-matplotlib.mp4 (14.21 MB)
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01 urllib-and-beautifulsoup.mp4 (26.87 MB)
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01 course-summary.mp4 (5.65 MB)
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01 Final Course1.zip (551.69 KB)
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02 course-materials Final Course4.zip (9.75 KB)
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01 introduction-to-recommender-systems.mp4 (11.54 MB)
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02 recommender-systems-versus-other-forms-of-supervised-learning.mp4 (16.85 MB)
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03 collaborative-filtering-based-recommendation.mp4 (40.31 MB)
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01 latent-factor-models-part-1.mp4 (25.21 MB)
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02 latent-factor-models-part-2.mp4 (21 MB)
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01 implementing-a-similarity-based-recommender.mp4 (19.38 MB)
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02 similarity-based-recommender-for-rating-prediction.mp4 (15.98 MB)
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01 implementing-a-latent-factor-model-part-1.mp4 (24.73 MB)
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02 implementing-a-latent-factor-model-part-2.mp4 (13.65 MB)
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01 intro-to-web-server-frameworks-in-python.mp4 (10.24 MB)
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02 intro-to-django.mp4 (12.03 MB)
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04 flask.mp4 (18.19 MB)
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01 project-description Final Course4.zip (9.75 KB)
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01 description-of-capstone-tasks.mp4 (12.87 MB)
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02 capstone-overview CAPSTONE.zip (9.14 KB)
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01 Final Course4.zip (9.75 KB)
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01 CAPSTONE.zip (8.94 KB)
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02 course-materials Final Course2.zip (23.09 MB)
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01 introduction-to-supervised-learning.mp4 (20 MB)
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01 introduction-to-supervised-learning Final Course2.zip (23.09 MB)
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02 supervised-learning-regression.mp4 (17.89 MB)
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02 supervised-learning-regression Final Course2.zip (23.09 MB)
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01 regression-in-python.mp4 (17.85 MB)
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01 regression-in-python Final Course2.zip (23.09 MB)
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02 time-series-regression.mp4 (17.76 MB)
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02 time-series-regression Final Course2.zip (23.09 MB)
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03 autoregression.mp4 (14.15 MB)
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03 autoregression Final Course2.zip (23.09 MB)
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01 features-from-categorical-data.mp4 (20.23 MB)
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01 features-from-categorical-data Final Course2.zip (23.09 MB)
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02 features-from-temporal-data.mp4 (17.35 MB)
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02 features-from-temporal-data Final Course2.zip (23.09 MB)
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03 feature-transformations.mp4 (9.74 MB)
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03 feature-transformations Final Course2.zip (23.09 MB)
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04 missing-values.mp4 (18 MB)
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04 missing-values Final Course2.zip (23.09 MB)
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01 supervised-learning-classification.mp4 (12 MB)
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01 supervised-learning-classification Final Course2.zip (23.09 MB)
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02 classification-nearest-neighbors.mp4 (9.75 MB)
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02 classification-nearest-neighbors Final Course2.zip (23.09 MB)
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03 classification-logistic-regression.mp4 (17.71 MB)
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03 classification-logistic-regression Final Course2.zip (23.09 MB)
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04 introduction-to-support-vector-machines.mp4 (19.79 MB)
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04 introduction-to-support-vector-machines Final Course2.zip (23.09 MB)
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01 classification-in-python.mp4 (13.7 MB)
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01 classification-in-python Final Course2.zip (23.09 MB)
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02 introduction-to-training-and-testing.mp4 (12.82 MB)
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02 introduction-to-training-and-testing Final Course2.zip (23.09 MB)
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01 gradient-descent-in-python.mp4 (16.48 MB)
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01 gradient-descent-in-python Final Course2.zip (23.09 MB)
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02 gradient-descent-in-tensorflow.mp4 (12.7 MB)
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02 gradient-descent-in-tensorflow Final Course2.zip (23.09 MB)
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03 livecoding-tensorflow.mp4 (9.62 MB)
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01 Final Course2.zip (23.09 MB)
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01 introduction-to-course-3-meaningful-predictive-modeling.mp4 (8.58 MB)
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01 course-materials Final Course3.zip (19.26 MB)
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01 motivation-behind-the-mse.mp4 (16.44 MB)
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02 regression-diagnostics-mse-and-r2.mp4 (13.27 MB)
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03 over-and-under-fitting.mp4 (13.09 MB)
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01 classification-diagnostics-accuracy-and-error.mp4 (21.15 MB)
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02 classification-diagnostics-precision-and-recall.mp4 (22.64 MB)
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01 setting-up-a-codebase-for-evaluation-and-validation.mp4 (25.35 MB)
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01 model-complexity-and-regularization.mp4 (20.5 MB)
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02 adding-a-regularizer-to-our-model-and-evaluating-the-regularized-model.mp4 (17.04 MB)
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03 evaluating-classifiers-for-ranking.mp4 (8.59 MB)
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01 validation.mp4 (9.73 MB)
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02 theorems-about-training-testing-and-validation.mp4 (16.91 MB)
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01 implementing-a-regularization-pipeline-in-python.mp4 (11.23 MB)
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02 guidelines-on-the-implementation-of-predictive-pipelines.mp4 (11.04 MB)
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Free search engine download: Coursera Python Data Products for Predictive Analytics Specialization

 

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775.45 MB | 00:13:36 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

01 introduction-to-the-program (28.77 MB)
02 instructor-introduction-video (8.37 MB)
01 approaching-data-analysis-with-the-osemn-framework (14.11 MB)
02 why-python-for-data-analysis (13.24 MB)
01 jupyter-notebook-where-we-write-our-code (3.04 MB)
02 basics-of-using-jupyter-notebook (8.76 MB)
03 using-jupyter-notebook-on-coursera (6.62 MB)
05 reviewing-example-of-a-typical-notebook-on-coursera-activity (10.13 MB)
01 what-does-a-variable-mean-in-python (21.26 MB)
02 variable-types (8.07 MB)
03 working-with-types-in-python (10.73 MB)
04 reviewing-variables-in-python-activity (2.5 MB)
01 lists-tuples (17.83 MB)
02 reviewing-lists-tuples-activity (10.17 MB)
03 dictionaries (11.4 MB)
04 reviewing-dictionaries-activity (6.72 MB)
01 booleans-in-python (9.88 MB)
02 reviewing-using-booleans-activity (7.8 MB)
03 conditional-statements (19.9 MB)
04 reviewing-using-conditionals-activity (7.74 MB)
01 introduction-to-libraries (12.43 MB)
01 what-is-pandas (16.47 MB)
02 working-with-pandas-series-dataframes (21.52 MB)
04 reviewing-pandas-activity (8.65 MB)
05 subsets-with-pandas (19.37 MB)
06 reviewing-selective-subsets-activity (7.39 MB)
01 what-is-scrubbing (7.17 MB)
02 removing-data (19.1 MB)
03 reviewing-removing-data-activity (10.08 MB)
04 modifying-values (12.28 MB)
05 replacing-values (8.18 MB)
06 reviewing-replacing-values-activity (13.62 MB)
01 why-exploration (7.08 MB)
01 exploring-relates-to-scrubbing (7.35 MB)
02 exploration-basic-statistics (17.95 MB)
03 exploration-filtering-data (25.4 MB)
04 reviewing-basic-exploration-activity (9.38 MB)
01 a-picture-is-worth-a-thousand-words (12.76 MB)
02 introduction-to-the-purpose-of-visualizations (5.69 MB)
03 types-of-exploratory-visualizations-distributions (13.92 MB)
04 types-of-exploratory-visualizations-category (9.4 MB)
05 types-of-exploratory-visualizations-relationship (12.41 MB)
06 using-pandas-and-matplotlib-to-create-visualizations (18.07 MB)
07 reviewing-creating-visualizations-activity (12.25 MB)
08 understanding-visualizations-for-exploration (14.91 MB)
09 reviewing-exploring-with-visualization-activity (9.84 MB)
01 where-aggregations-help-us-understand-data (8.3 MB)
02 working-with-groups-in-pandas (22.25 MB)
03 reviewing-aggregations-activity (6.53 MB)
01 modeling-interpreting-data (6.33 MB)
02 overview-of-modeling (12.99 MB)
03 modeling-with-python (28.92 MB)
01 overview-of-interpreting (20.61 MB)
02 interpreting-model-results (16.54 MB)
03 exploratory-vs-explanatory-visualizations (13.72 MB)
04 creating-explanatory-visualizations (20.23 MB)
01 osemn-tying-it-all-together (28.9 MB)
02 reviewing-full-osemn-activity (28.63 MB)

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