{"id":24510550,"url":"https://github.com/lim-calculus/sequence-time-seires-and-predictions","last_synced_at":"2025-03-15T09:41:09.781Z","repository":{"id":65254686,"uuid":"589065632","full_name":"Lim-Calculus/Sequence-Time-Seires-and-Predictions","owner":"Lim-Calculus","description":"My Solution to DeepLearning.AI TensorFlow Developer Certificate Course 4 : Sequence, Time Seires and Predictions","archived":false,"fork":false,"pushed_at":"2023-01-25T03:19:50.000Z","size":3559,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-01-22T00:34:12.081Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Lim-Calculus.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2023-01-14T23:49:43.000Z","updated_at":"2023-01-15T01:15:59.000Z","dependencies_parsed_at":"2023-02-14T04:16:07.499Z","dependency_job_id":null,"html_url":"https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lim-Calculus%2FSequence-Time-Seires-and-Predictions","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lim-Calculus%2FSequence-Time-Seires-and-Predictions/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lim-Calculus%2FSequence-Time-Seires-and-Predictions/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lim-Calculus%2FSequence-Time-Seires-and-Predictions/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Lim-Calculus","download_url":"https://codeload.github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243713391,"owners_count":20335566,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-01-22T00:29:40.679Z","updated_at":"2025-03-15T09:41:09.743Z","avatar_url":"https://github.com/Lim-Calculus.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sequence-Time-Seires-and-Predictions\nMy Solution to DeepLearning.AI TensorFlow Developer Certificate Course 4 : Sequence, Time Seires and Predictions\n# Week 1\n## Time Series\n- Time Series typically defined as an ordered sequence of values that are usually equally spaced overtime\n- Univariate Time Series : a single value at each time step\n![Univariate Time Series](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_Univariate_Time_Series.png)\n- Multivariate Time Series : time series that have multiple values at each time step \n![Multivariate Time Series](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_Multivariate_Time_Series.png)\n- Imputation :  In statistics, imputation is the process of replacing missing data with substituted values. When substituting for a data point, it is known as \"unit imputation\"; when substituting for a component of a data point, it is known as \"item imputation\"\n![Imputation in Moore's Law](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_Moore'sLaw_ImputedData.png)\n![Week1_ImputedData.png](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_ImputedData.png)\n\n## Common Pattern in Time Series\n- Trend : Where time series have a specific direction that they are moving (Example : Moore's Law)\n- Seasonality : pattern repeat at predictable intervals\n![Week1_Seasonality.png](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_Seasonality.png)\n- White noise : random value\n- Autocorrelation :  it correlates with a delayed copy of itself often called a lag\n![Week1_Autocorrelation.png](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_Autocorrelation.png)\n## Train, Val, Test\n- Splitting the time series into training, validation and test period\n![Week1_TrainValTest.png](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_TrainValTest.png)\n## Metrics FOr Evaluating Performance\n![Week1_MetricsForEvaluatingPerformance.png](https://github.com/Lim-Calculus/Sequence-Time-Seires-and-Predictions/blob/main/Images/Week1_MetricsForEvaluatingPerformance.png)\n# Week 3 - Recurrent Neural Network in Time Series Predictions\n## Recurrent Neural Network : A recurrent neural network (RNN) is a special type of artificial neural network adapted to work for time series data or data that involves sequences.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flim-calculus%2Fsequence-time-seires-and-predictions","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flim-calculus%2Fsequence-time-seires-and-predictions","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flim-calculus%2Fsequence-time-seires-and-predictions/lists"}