392 skills found · Page 8 of 14
6matko / Tradeup NinjaComplete source code of Tradeup.Ninja project. Includes NestJS backend and Angular served via SSR.
akareen / AFL Data AnalysisA complete source for data and code to analyse the Australian Football League (AFL)
GylanSalih / Portify PortfolioComplete source code for my personal portfolio website, built with Next.js 🚀. It’s a modern, fully responsive portfolio that highlights my skills, projects, and professional experience. Don’t miss out - updates are made daily! ✨
Pfrommer1982 / Complete PortfolioA complete react portfolio website where you can fill in your info and you're done!
BlockchainLabs / SaluSReserve funds will be used to increase NAV by various means, including but not limited to investing in other coins, by trade or buy back. ICO: Crowdfunding & Price Discovery: Total BTC raised during the crowdfunding will act as the price discovery mechanism. 1,000,000 Salus will be distributed among investors based on percentage invested. My share of SLS will based on total value of coins listed within Kick Starter and Trading Coins at the end of ICO. Crowdfunding phase extended to 1-18-2016 The first 10 supporters/participants will receive 10% bonus SaluS coin after distribution is over. The next 10 participants will receive 5% extra SLS. Participation requires minimum of 0.01 BTC. Crowdfunding Address: Quote 1LJPiY3vUeN5SkLY9k8qBHeMdBeXJNNtBe and Form:http://goo.gl/forms/0cMMy02srh Must be completed. Make sure to send from an address you control, not an exchange. Total Collected:https://blockchain.info/address/1LJPiY3vUeN5SkLY9k8qBHeMdBeXJNNtBe Or Use escrow Escrow Instructions: https://bitcointalk.org/index.php?topic=1317448.msg13471975#msg13471975 Kick Starter Coins: HyperStake RateCoin AudioCoin Noble Redd Viral PebbleCoin PeerCoin HYP XRA ADC NOBL RDD VIRAL XPB PPC 7,000,000: 4,000,000: 20,000,000: 70,000,000: 20,000,000: 100,000: 150,000: 100: Trading coins: BitShare Burst NXT SiaCoin XEM Dashcoin Horizon Florin Quatloo Monero BTS BURST NXT SIA XEM DSH HZ FLO QTL XMR 50,000 5,000,000 100,000 20,000,000 1,000,000 100,000 500,000 100,000 10,000 200 Cloud Staking Service: - Coin Request Form - http://goo.gl/forms/30P0We6pke HyperStake RateCoin AudioCoin Noble Redd Viral RUBY HYP XRA ADC NOBL RDD VIRAL RBY http://goo.gl/forms/Yyaub9a5aX http://goo.gl/forms/161pSKoC6Y http://goo.gl/forms/M1AG1YCinF http://goo.gl/forms/qXMhkzxdCn http://goo.gl/forms/LrAAE6kVFM http://goo.gl/forms/ZF1z6MgRYN http://goo.gl/forms/FV98Be3ZPq AFFILIATE PROGRAMS: Affiliate Program Submission form-http://goo.gl/forms/6bujSMhkgM Exchanges: Coinbase localbitcoins Bleutrade 1Broker https://www.coinbase.com/join/ https://localbitcoins.com/? https://bleutrade.com/sign_up/ https://1broker.com/m/r.php Mining: MinerGate LTCrabbit CoinKing.io https://minergate.com/ https://www.ltcrabbit.com/ http://coinking.io/? Hosting/VPS/VPN/Domains: NameCheap BitDomain.BIZ BitVPN.org http://www.namecheap.com/? http://www.bitdomain.biz/? https://bitvpn.org/? Gaming: BC Casino Directbet.eu Bitcasino.io Betterbet.io DigiByte https://www.bc-casino.com/? http://www.directbet.eu? http://coinpoker.io? https://betterbets.io/? http://www.digibytegaming.com/users/sign_up? Interest paying Wallets BW.com https://bw.com/ MISC. cointracking.info FreeDogeCoin FreeBitcoin http://cointracking.info http://freedoge.co.in/? http://freebitco.in/? Consumer Goods: Compiling List. PM me on BCT, Slack or IRC if you have any question, concerns or suggestions. Special Thanks: Syntaks - wallet Presstab - Block Explorer/Code review SebastianJu - Escrow Stoner19 - Feedback/Pool/All around help. iDunk - Win64 wallet Billotronic - MAC wallet ozmaster - Advice/Coinbar Listing Drew - IRC Bot And everyone else that has been supportive of this project.| Coin Specifications Coin Name - SaluS Ticker - SLS Annual Interest - 1% Supply - 1,000,000 Min stake age - 8 hours Max stake age - No Max age SaluS Fund Transaction Fee - .0001 Block Time - 3Min Block maturity - 5 p2p Port - 22534 rpc port - 22530 50 confirm stake minimum for eligibility (Wallet was developed by Syntaks)- https://bitcointalk.org/index.php?action=profile;u=175669 (BlockExplorer provided by Presstab)- http://www.presstab.pw/ Logo- http://saluscoin.info/pics/sls.png Source- https://github.com/saluscoin/SaluS Wallet - Win 32 | Win 64 | Raspi | Mac Block Explorer- http://sls.presstab.pw Nodes:http://www.presstab.pw/phpexplorer/SLS/nodes.php Exchanges: Bittrex - https://stage.bittrex.com/Market/Index?MarketName=BTC-SLS YoBit - https://yobit.net/en/trade/SLS/BTC Vote: - https://c-cex.com/?id=vote&coin=sls PM me if interest in adding SLS to your exchange Faucet: http://crypto-faucet.eu/faucets/sls About: An experimental Coin aimed to increase Net Asset Value (NAV) by various means. Kick Starter Coins: Below is a list of coins that will be included during the initial phase of this project. Listed coins will stake on behalf of SaluS project, stakes will be sold on exchanges to increase BTC reserve. Cloud Staking Service: Fees will be 5% of the stakes, however, the advantages listed below easily outweigh the fees. 1) Experience, keen knowledge of Coin specs. 2) Customized wallets for optimum stacking 3) Staking Advantage, (whaling weight/diff), Research for Optimum block size. 4) 24/7 Uptime, No Hassle, no worry, No Resource staking. Affiliate programs: All profit made from affiliate programs will go to SaluS reserve to increase NAV. If you hold Salus coin and would like to help your investment grow, sign up for the services listed below using provided links. Foundation Transaction Fee - .0001 This is a separate TX fee of .0001 that goes to a specific Address, called the Foundation Transaction fee. This fee is in place for couple of reasons. 1) To control inflation since the supply is set to increase by 1% annually. 2) Resold to increase the reserve. Mining Guaranteed Minimum CPU hash rate of 1000H/s Would encourage everyone invested in this coin with CPU power to spare, to click on the link below. link will be up soon. Traders Advantage: Top 10 Claimed Addresses on the rich list will have access to all trades and portfolio activity/status in near real time. There will be a fee for those who are not on top 10 list but would like to have access to such information. All fees will be added to the reserve fund. MultiPool: http://hashgoal.com/ "Holy Grail" - Financial Instrument Will not disclose any information about this project at this time, but I do believe this will take SaluS to a whole new level if it gets off the ground. (details on this project will be announced as soon as development officially starts)
NimbleUser / Apex Style GuideThis repository contains the complete definition of NimbleUser's coding standards for source code in the Apex Programming Language on the Salesforce Force.com platform
travens-id / Bangkit Machine LearningThe source code of machine learning model's API of Travens smart guide in order to complete Bangkit Capstone Project
maks-it / CMake TutorialBelow is a step-by-step tutorial covering common build system use cases that CMake helps to address. Many of these topics have been introduced in Mastering CMake as separate issues but seeing how they all work together in an example project can be very helpful. This tutorial can be found in the Tests/Tutorial directory of the CMake source code tree. Each step has its own subdirectory containing a complete copy of the tutorial for that step.
rocklegend-org / WebsiteThe complete rocklegend.org source code of the current rocklegend version.
bharathirajatut / Ionic3This repository contains complete source code for Ionic 3 tutorial from https://ampersandacademy.com/tutorials/ionic-framework-3. I will try many Ionic 3 specific scripts and will write them as separate tutorial. You can follow this repo to get more tested and working script for the Ionic 3.
ultranet1 / APACHE AIRFLOW DATA PIPELINESProject Description: A music streaming company wants to introduce more automation and monitoring to their data warehouse ETL pipelines and they have come to the conclusion that the best tool to achieve this is Apache Airflow. As their Data Engineer, I was tasked to create a reusable production-grade data pipeline that incorporates data quality checks and allows for easy backfills. Several analysts and Data Scientists rely on the output generated by this pipeline and it is expected that the pipeline runs daily on a schedule by pulling new data from the source and store the results to the destination. Data Description: The source data resides in S3 and needs to be processed in a data warehouse in Amazon Redshift. The source datasets consist of JSON logs that tell about user activity in the application and JSON metadata about the songs the users listen to. Data Pipeline design: At a high-level the pipeline does the following tasks. Extract data from multiple S3 locations. Load the data into Redshift cluster. Transform the data into a star schema. Perform data validation and data quality checks. Calculate the most played songs for the specified time interval. Load the result back into S3. dag Structure of the Airflow DAG Design Goals: Based on the requirements of our data consumers, our pipeline is required to adhere to the following guidelines: The DAG should not have any dependencies on past runs. On failure, the task is retried for 3 times. Retries happen every 5 minutes. Catchup is turned off. Do not email on retry. Pipeline Implementation: Apache Airflow is a Python framework for programmatically creating workflows in DAGs, e.g. ETL processes, generating reports, and retraining models on a daily basis. The Airflow UI automatically parses our DAG and creates a natural representation for the movement and transformation of data. A DAG simply is a collection of all the tasks you want to run, organized in a way that reflects their relationships and dependencies. A DAG describes how you want to carry out your workflow, and Operators determine what actually gets done. By default, airflow comes with some simple built-in operators like PythonOperator, BashOperator, DummyOperator etc., however, airflow lets you extend the features of a BaseOperator and create custom operators. For this project, I developed several custom operators. operators The description of each of these operators follows: StageToRedshiftOperator: Stages data to a specific redshift cluster from a specified S3 location. Operator uses templated fields to handle partitioned S3 locations. LoadFactOperator: Loads data to the given fact table by running the provided sql statement. Supports delete-insert and append style loads. LoadDimensionOperator: Loads data to the given dimension table by running the provided sql statement. Supports delete-insert and append style loads. SubDagOperator: Two or more operators can be grouped into one task using the SubDagOperator. Here, I am grouping the tasks of checking if the given table has rows and then run a series of data quality sql commands. HasRowsOperator: Data quality check to ensure that the specified table has rows. DataQualityOperator: Performs data quality checks by running sql statements to validate the data. SongPopularityOperator: Calculates the top ten most popular songs for a given interval. The interval is dictated by the DAG schedule. UnloadToS3Operator: Stores the analysis result back to the given S3 location. Code for each of these operators is located in the plugins/operators directory. Pipeline Schedule and Data Partitioning: The events data residing on S3 is partitioned by year (2018) and month (11). Our task is to incrementally load the event json files, and run it through the entire pipeline to calculate song popularity and store the result back into S3. In this manner, we can obtain the top songs per day in an automated fashion using the pipeline. Please note, this is a trivial analyis, but you can imagine other complex queries that follow similar structure. S3 Input events data: s3://<bucket>/log_data/2018/11/ 2018-11-01-events.json 2018-11-02-events.json 2018-11-03-events.json .. 2018-11-28-events.json 2018-11-29-events.json 2018-11-30-events.json S3 Output song popularity data: s3://skuchkula-topsongs/ songpopularity_2018-11-01 songpopularity_2018-11-02 songpopularity_2018-11-03 ... songpopularity_2018-11-28 songpopularity_2018-11-29 songpopularity_2018-11-30 The DAG can be configured by giving it some default_args which specify the start_date, end_date and other design choices which I have mentioned above. default_args = { 'owner': 'shravan', 'start_date': datetime(2018, 11, 1), 'end_date': datetime(2018, 11, 30), 'depends_on_past': False, 'email_on_retry': False, 'retries': 3, 'retry_delay': timedelta(minutes=5), 'catchup_by_default': False, 'provide_context': True, } How to run this project? Step 1: Create AWS Redshift Cluster using either the console or through the notebook provided in create-redshift-cluster Run the notebook to create AWS Redshift Cluster. Make a note of: DWN_ENDPOINT :: dwhcluster.c4m4dhrmsdov.us-west-2.redshift.amazonaws.com DWH_ROLE_ARN :: arn:aws:iam::506140549518:role/dwhRole Step 2: Start Apache Airflow Run docker-compose up from the directory containing docker-compose.yml. Ensure that you have mapped the volume to point to the location where you have your DAGs. NOTE: You can find details of how to manage Apache Airflow on mac here: https://gist.github.com/shravan-kuchkula/a3f357ff34cf5e3b862f3132fb599cf3 start_airflow Step 3: Configure Apache Airflow Hooks On the left is the S3 connection. The Login and password are the IAM user's access key and secret key that you created. Basically, by using these credentials, we are able to read data from S3. On the right is the redshift connection. These values can be easily gathered from your Redshift cluster connections Step 4: Execute the create-tables-dag This dag will create the staging, fact and dimension tables. The reason we need to trigger this manually is because, we want to keep this out of main dag. Normally, creation of tables can be handled by just triggering a script. But for the sake of illustration, I created a DAG for this and had Airflow trigger the DAG. You can turn off the DAG once it is completed. After running this DAG, you should see all the tables created in the AWS Redshift. Step 5: Turn on the load_and_transform_data_in_redshift dag As the execution start date is 2018-11-1 with a schedule interval @daily and the execution end date is 2018-11-30, Airflow will automatically trigger and schedule the dag runs once per day for 30 times. Shown below are the 30 DAG runs ranging from start_date till end_date, that are trigged by airflow once per day. schedule
NestieGuilas / Marketing Platform Marketing Platform Google Analytics Terms of Service These Google Analytics Terms of Service (this "Agreement") are entered into by Google LLC ("Google") and the entity executing this Agreement ("You"). This Agreement governs Your use of the standard Google Analytics (the "Service"). BY CLICKING THE "I ACCEPT" BUTTON, COMPLETING THE REGISTRATION PROCESS, OR USING THE SERVICE, YOU ACKNOWLEDGE THAT YOU HAVE REVIEWED AND ACCEPT THIS AGREEMENT AND ARE AUTHORIZED TO ACT ON BEHALF OF, AND BIND TO THIS AGREEMENT, THE OWNER OF THIS ACCOUNT. In consideration of the foregoing, the parties agree as follows: 1. Definitions. "Account" refers to the account for the Service. All Profiles (as applicable) linked to a single Property will have their Hits aggregated before determining the charge for the Service for that Property. 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This Agreement (including any amendment agreed upon by the parties in writing) represents the complete agreement between You and Google concerning its subject matter, and supersedes all prior agreements and representations between the parties. If any provision of this Agreement is held to be unenforceable for any reason, such provision will be reformed to the extent necessary to make it enforceable to the maximum extent permissible so as to effect the intent of the parties, and the remainder of this Agreement will continue in full force and effect. This Agreement will be governed by and construed under the laws of the state of California without reference to its conflict of law principles. In the event of any conflicts between foreign law, rules, and regulations, and California law, rules, and regulations, California law, rules and regulations will prevail and govern. Each party agrees to submit to the exclusive and personal jurisdiction of the courts located in Santa Clara County, California. The United Nations Convention on Contracts for the International Sale of Goods and the Uniform Computer Information Transactions Act do not apply to this Agreement. The Software is controlled by U.S. Export Regulations, and it may be not be exported to or used by embargoed countries or individuals. Any notices to Google must be sent to: Google LLC, 1600 Amphitheatre Parkway, Mountain View, CA 94043, USA, with a copy to Legal Department, via first class or air mail or overnight courier, and are deemed given upon receipt. A waiver of any default is not a waiver of any subsequent default. You may not assign or otherwise transfer any of Your rights in this Agreement without Google's prior written consent, and any such attempt is void. The relationship between Google and You is not one of a legal partnership relationship, but is one of independent contractors. This Agreement will be binding upon and inure to the benefit of the respective successors and assigns of the parties hereto. The following sections of this Agreement will survive any termination thereof: 1, 4, 5, 6 (except the last two sentences), 7, 8, 9, 10, 11, 12, 14, 16, and 17. 17. Google Analytics for Firebase. If You link a Property to Firebase (“Firebase Linkage”) as part of using the Service, the following terms, in addition to Sections 1-16 above, will also apply to You, and will also govern Your use of the Service, including with respect to Your use of Firebase Linkage. Other than as modified below, all other terms will stay the same and continue to apply. In the event of a conflict between this Section 17 and Sections 1-16 above, the terms in Section 17 will govern and control solely with respect to Your use of the Firebase Linkage. The following definition in Section 1 is modified as follows: "Hit" means a collection of interactions that results in data being sent to the Service and processed. Examples of Hits may include page view hits and ecommerce hits. A Hit can be a call to the Service by various libraries, but does not have to be so (e.g., a Hit can be delivered to the Service by other Google Analytics-supported protocols and mechanisms made available by the Service to You). For the sake of clarity, a Hit does not include certain events whose collection reflects interactions with certain Properties capable of supporting multiple data streams, and which may include screen views and custom events (the collection of events, an “Enhanced Packet”). The following sentence is added to the end of Section 7 as follows: If You link a Property to a Firebase project (“Firebase Linkage”) (i) certain data from Your Property, including Customer Data, may be made accessible within or to any other entity or personnel according to permissions set in Firebase and (ii) that Property may have certain Service settings modified by authorized personnel of Firebase (notwithstanding the settings You may have designated for that Property within the Service). 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