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| 001. Getting started.en.srt |
2.29Кб |
| 001. Getting started.mp4 |
13.80Мб |
| 002. Supply and demand for data science.en.srt |
6.43Кб |
| 002. Supply and demand for data science.mp4 |
39.12Мб |
| 003. The data science Venn diagram.en.srt |
7.54Кб |
| 003. The data science Venn diagram.mp4 |
39.30Мб |
| 004. The data science pathway.en.srt |
8.88Кб |
| 004. The data science pathway.mp4 |
58.40Мб |
| 005. The CRISP-DM model in data science.en.srt |
6.04Кб |
| 005. The CRISP-DM model in data science.mp4 |
35.20Мб |
| 006. Roles and teams in data science.en.srt |
7.73Кб |
| 006. Roles and teams in data science.mp4 |
38.73Мб |
| 007. The role of questions in data science.en.srt |
7.52Кб |
| 007. The role of questions in data science.mp4 |
42.13Мб |
| 008. Artificial intelligence.en.srt |
13.42Кб |
| 008. Artificial intelligence.mp4 |
73.01Мб |
| 009. Machine learning.en.srt |
13.10Кб |
| 009. Machine learning.mp4 |
96.85Мб |
| 010. Deep learning neural networks.en.srt |
13.40Кб |
| 010. Deep learning neural networks.mp4 |
72.46Мб |
| 011. Big data.en.srt |
9.12Кб |
| 011. Big data.mp4 |
49.05Мб |
| 012. Predictive analytics.en.srt |
8.21Кб |
| 012. Predictive analytics.mp4 |
43.03Мб |
| 013. Prescriptive analytics.en.srt |
13.21Кб |
| 013. Prescriptive analytics.mp4 |
66.36Мб |
| 014. Business intelligence.en.srt |
6.98Кб |
| 014. Business intelligence.mp4 |
40.38Мб |
| 015. Bias.en.srt |
10.58Кб |
| 015. Bias.mp4 |
57.39Мб |
| 016. Security.en.srt |
8.81Кб |
| 016. Security.mp4 |
47.85Мб |
| 017. Legal.en.srt |
10.69Кб |
| 017. Legal.mp4 |
58.60Мб |
| 018. Explainable AI.en.srt |
16.10Кб |
| 018. Explainable AI.mp4 |
86.49Мб |
| 019. Agency of algorithms and decision-makers.en.srt |
8.57Кб |
| 019. Agency of algorithms and decision-makers.mp4 |
42.23Мб |
| 020. Data preparation.en.srt |
8.70Кб |
| 020. Data preparation.mp4 |
47.63Мб |
| 021. Labeling data.en.srt |
17.07Кб |
| 021. Labeling data.mp4 |
76.36Мб |
| 022. In-house data.en.srt |
9.90Кб |
| 022. In-house data.mp4 |
49.30Мб |
| 023. Open data.en.srt |
7.04Кб |
| 023. Open data.mp4 |
37.31Мб |
| 024. APIs.en.srt |
4.44Кб |
| 024. APIs.mp4 |
23.66Мб |
| 025. Scraping data.en.srt |
8.08Кб |
| 025. Scraping data.mp4 |
57.03Мб |
| 026. Creating data.en.srt |
9.66Кб |
| 026. Creating data.mp4 |
49.07Мб |
| 027. Passive collection of training data.en.srt |
6.80Кб |
| 027. Passive collection of training data.mp4 |
34.59Мб |
| 028. Self-generated data.en.srt |
5.48Кб |
| 028. Self-generated data.mp4 |
42.31Мб |
| 029. Data vendors.en.srt |
9.13Кб |
| 029. Data vendors.mp4 |
48.23Мб |
| 030. Data ethics.en.srt |
8.66Кб |
| 030. Data ethics.mp4 |
45.58Мб |
| 031. The enumeration of explicit rules.en.srt |
6.63Кб |
| 031. The enumeration of explicit rules.mp4 |
35.63Мб |
| 032. The derivation of rules from data analysis.en.srt |
7.19Кб |
| 032. The derivation of rules from data analysis.mp4 |
53.62Мб |
| 033. The generation of implicit rules.en.srt |
5.83Кб |
| 033. The generation of implicit rules.mp4 |
31.23Мб |
| 034. Applications for data analysis.en.srt |
7.47Кб |
| 034. Applications for data analysis.mp4 |
42.72Мб |
| 035. Languages for data science.en.srt |
5.98Кб |
| 035. Languages for data science.mp4 |
34.41Мб |
| 036. AutoML.en.srt |
6.79Кб |
| 036. AutoML.mp4 |
37.52Мб |
| 037. Machine learning as a service.en.srt |
5.63Кб |
| 037. Machine learning as a service.mp4 |
29.26Мб |
| 038. Sampling and probability.en.srt |
7.94Кб |
| 038. Sampling and probability.mp4 |
47.25Мб |
| 039. Algebra.en.srt |
12.73Кб |
| 039. Algebra.mp4 |
64.15Мб |
| 040. Calculus.en.srt |
7.69Кб |
| 040. Calculus.mp4 |
44.25Мб |
| 041. Optimization and the combinatorial explosion.en.srt |
10.97Кб |
| 041. Optimization and the combinatorial explosion.mp4 |
53.55Мб |
| 042. Bayes' theorem.en.srt |
7.21Кб |
| 042. Bayes' theorem.mp4 |
38.73Мб |
| 043. Supervised vs. unsupervised learning.en.srt |
5.86Кб |
| 043. Supervised vs. unsupervised learning.mp4 |
31.77Мб |
| 044. Descriptive analyses.en.srt |
11.90Кб |
| 044. Descriptive analyses.mp4 |
57.76Мб |
| 045. Clustering.en.srt |
10.43Кб |
| 045. Clustering.mp4 |
50.29Мб |
| 046. Dimensionality reduction.en.srt |
9.46Кб |
| 046. Dimensionality reduction.mp4 |
49.36Мб |
| 047. Anomaly detection.en.srt |
8.81Кб |
| 047. Anomaly detection.mp4 |
43.81Мб |
| 048. Supervised learning with predictive models.en.srt |
13.11Кб |
| 048. Supervised learning with predictive models.mp4 |
65.18Мб |
| 049. Time-series data.en.srt |
15.41Кб |
| 049. Time-series data.mp4 |
80.54Мб |
| 050. Classifying.en.srt |
9.89Кб |
| 050. Classifying.mp4 |
48.69Мб |
| 051. Feature selection and creation.en.srt |
10.39Кб |
| 051. Feature selection and creation.mp4 |
50.94Мб |
| 052. Aggregating models.en.srt |
14.10Кб |
| 052. Aggregating models.mp4 |
74.43Мб |
| 053. Validating models.en.srt |
9.29Кб |
| 053. Validating models.mp4 |
50.52Мб |
| 054. Generative adversarial networks (GANs).en.srt |
8.84Кб |
| 054. Generative adversarial networks (GANs).mp4 |
51.09Мб |
| 055. Reinforcement learning.en.srt |
10.28Кб |
| 055. Reinforcement learning.mp4 |
52.80Мб |
| 056. The importance of interpretability.en.srt |
5.60Кб |
| 056. The importance of interpretability.mp4 |
28.90Мб |
| 057. Interpretable methods.en.srt |
8.37Кб |
| 057. Interpretable methods.mp4 |
44.23Мб |
| 058. Actionable insights.en.srt |
4.76Кб |
| 058. Actionable insights.mp4 |
25.48Мб |
| 059. Next steps and additional resources.en.srt |
4.41Кб |
| 059. Next steps and additional resources.mp4 |
24.63Мб |
| Bonus Resources.txt |
386б |
| Get Bonus Downloads Here.url |
178б |