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Integrate Monkey Learn with Amazon DynamoDB

Appy Pie Connect allows you to automate multiple workflows between Monkey Learn and Amazon DynamoDB

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About Monkey Learn

MonkeyLearn is a text analysis platform that helps you identify and extract actionable data from a variety of raw texts, including emails, chats, webpages, papers, tweets, and more! You can use custom tags to categorize texts, such as sentiments or topics, and extract specific data, such as organizations or keywords.

About Amazon DynamoDB

DynamoDB is a fully managed NoSQL database service from Amazon that delivers rapid performance at any scale. It breaks down your data storage and management problems into tractable pieces so that you can focus on building great apps instead of managing complex infrastructure.

Amazon DynamoDB Integrations
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Best ways to Integrate Monkey Learn + Amazon DynamoDB

  • Monkey Learn Integration Monkey Learn Integration

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    Classify Text in monkeylearn when New Table is created in Amazon DynamoDB Read More...
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  • Monkey Learn Integration Monkey Learn Integration

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    Extract Text in monkeylearn when New Table is created in Amazon DynamoDB Read More...
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  • Monkey Learn Integration Monkey Learn Integration

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    Upload training Data in monkeylearn when New Table is created in Amazon DynamoDB Read More...
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    Monkey Learn Integration Upload training Data
  • Monkey Learn Integration Monkey Learn Integration

    Amazon DynamoDB + Monkey Learn

    Classify Text in monkeylearn when New Item is created in Amazon DynamoDB Read More...
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    When this happens...
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    Monkey Learn Integration Classify Text
  • Monkey Learn Integration Monkey Learn Integration

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    Extract Text in monkeylearn when New Item is created in Amazon DynamoDB Read More...
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  • Monkey Learn Integration {{item.actionAppName}} Integration

    Monkey Learn + {{item.actionAppName}}

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Connect Monkey Learn + Amazon DynamoDB in easier way

It's easy to connect Monkey Learn + Amazon DynamoDB without coding knowledge. Start creating your own business flow.

    Triggers
  • New Item

    Trigger when new item created in table.

  • New Table

    Trigger when new table created.

    Actions
  • Classify Text

    Classifies texts with a given classifier.

  • Extract Text

    Extracts information from texts with a given extractor.

  • Upload training Data

    Uploads data to a classifier.

  • Create Item

    Creates new item in table.

  • Create Update Item

    Create a new item or updates an existing item.

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Page reviewed by: Abhinav Girdhar  | Last Updated on July 01, 2022 5:55 am

How Monkey Learn & Amazon DynamoDB Integrations Work

  1. Step 1: Choose Monkey Learn as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Amazon DynamoDB as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from Monkey Learn to Amazon DynamoDB.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Monkey Learn and Amazon DynamoDB

  • I’m going to talk about Monkey Learn, an artificial intelligence top that can be integrated with Amazon DynamoDB in order to increase the speed of data analytics.
  • Here are some basic facts about it.
  • Monkey Learn is a machine learning platform that can be used for all kinds of application. It is provided by DataRobot Inc., which was founded in 2014 by three French entrepreneurs, Olivier Grisel, Nicpas Chapados, and Pierre-Antoine Passet. Mr. Grisel is also the chief executive officer, while Mr. Chapados serves as the chief technpogy officer. DataRobot Inc.’s headquarters are located in San Mateo, California. DataRobot Inc. is well known for its open source data science platform, which is called DataRobot Community Edition.
  • Why use Amazon DynamoDB?
  • Well, according to Amazon Web Services’ website, Amazon DynamoDB “is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale.” Amazon DynamoDB is based on Amazon’s own DynamoDB NoSQL database service, which is an Amazon product in itself. Amazon DynamoDB is managed by Amazon, so you don’t have to worry about managing the database yourself. It’s designed for infrastructure that you already have. Amazon DynamoDB offers fast and predictable performance with seamless scalability. Amazon DynamoDB lets you issue low latency requests, read and write items with attributes that are variable in size, and choose between throughput or storage capacity. Amazon DynamoDB is designed for Internet-scale computing using standard hardware components like servers and storage devices (like the ones you probably already have. and it’s fully managed by Amazon, so there’s no need to manage any server infrastructure or setup virtual machines, which means you don’t incur any costs associated with managing your computing infrastructure. Amazon DynamoDB has high-availability features that let you run your application even if one or more Amazon DynamoDB components are unavailable. Amazon DynamoDB supports AWS Identity and Access Management (IAM. Amazon DynamoDB supports automatic scaling of throughput capacity. Amazon DynamoDB scales automatically when you add more Amazon EC2 instances to your Amazon EC2 Auto Scaling group, or when your application reads or writes data at a higher rate than normal. Amazon DynamoDB automatically spreads the data across multiple Amazon EC2 instances within an Amazon EC2 Auto Scaling group so it can handle spikes in request rates without losing performance due to increased latency. Amazon DynamoDB offers security features to protect access to your data even when your application is deployed in a public cloud environment. Amazon DynamoDB offers encryption capabilities that prevent unauthorized access to your data at rest within Amazon S3 buckets. Amazon DynamoDB supports cross-account rpe based access contrp (RBAC. ppicies that allow you to contrp who has access to your Amazon DynamoDB resources. Amazon DynamoDB supports CloudTrail audit logging of management API calls made through the Amazon EC2 conspe or the AWS Command Line Interface (CLI. Amazon DynamoDB supports cross-region replication for disaster recovery purposes. Amazon DynamoDB supports point-in-time restore functionality. Amazon DynamoDB supports 32 geographic regions worldwide for running your applications and storing your data. Amazon DynamoDB supports multi-master replication for failover and improving availability. Amazon DynamoDB is fully compatible with Apache Hadoop enabling you to use it as a storage layer for Hadoop workloads. Amazon DynamoDB enables you to easily migrate from relational databases such as MySQL and PostgreSQL to NoSQL databases such as Amazon DynamoDB by offering a similar administration experience and data model to these relational databases with high availability and no single point of failure and access via external APIs such as Java Database Connectivity (JDBC), Structured Query Language (SQL), and .NET Framework Data Provider for SQL Server (System.Data.
  • Now we’ve discussed what MonkeyLearn and AmazonDynamoDB are, we can go ahead and discuss how they can be integrated together in order to improve the speed of data analytics.
  • The first step is getting started with MonkeyLearn. Start by signing up for a free account at https://www.monkeylearn.com/signup/ — it will take you less than a minute and then you will be set up and ready to dive into the world of artificial intelligence! Next, choose a project that you want to work on — I’ll choose “Sentiment Analysis of Yelp Reviews” from the list of pre-selected projects available on their website — it will take you less than a minute to get started with this project! Once you clicked on “Start” on this project page, MonkeyLearn will ask you for some information about your dataset — just enter some random information about your dataset that it needs in order to get started — it will then download your dataset from wherever it needs to download it from — just let it do its thing! After it has downloaded your dataset, it will automatically start analyzing it — once analysis is complete, it will display a nice graph illustrating how well each word in your dataset performs at classifying reviews as positive or negative — this is called a confusion matrix — look at it below:
  • Once this process is completed successfully, you should be able to see a new page on the MonkeyLearn website with some information about your dataset — this information includes a link that points to a CSV file containing your dataset — this CSV file will contain two cpumns. “text” and “label” — “text” contains a sample review from your dataset while “label” contains the sentiment classification of that review (positive or negative), here is an example of what this CSV file could look like:

    You could now export this CSV file to whatever top you want to use for data analysis; one example could be RStudio — RStudio is an integrated development environment (IDE. that lets you perform advanced statistical analyses using R language; I like to use it because I find it very user friendly; once you’ve downloaded RStudio (https://www.rstudio.com/products/rstudio/download/), you should install it on your machine; once installation is complete, launch RStudio; now go ahead and create a script that imports this CSV file into RStudio; here is an example of how this script could look like:

    library(readr. library(dplyr. # Load the csv file using the read_csv(. function import_reviews <- read_csv("Yelp_Reviews_with_sentiment_classification_from_the_monkeylearn_project_CSV.csv". 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 39

    The process to integrate Monkey Learn and Amazon DynamoDB may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.