Building Bad Titles For Talks
Published: 2021-09-02 14:17:42

---
title: Building Bad Titles For Talks
published: true
date: 2021-08-02 14:50:00 UTC
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---

 **Building Bad Titles For Talks**

**gentitles.pt**

from textgenrnn import textgenrnn

textgen = textgenrnn()

textgen.train\_from\_file('tim.txt', num\_epochs=1)

textgen.generate()

 

**Example Run**

tspann@Timothys-MBP code % python3.7 gentitles.py

/Users/tspann/Library/Python/3.7/lib/python/site-packages/tensorflow/python/keras/optimizer\_v2/optimizer\_v2.py:375: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.

  "The `lr` argument is deprecated, use `learning_rate` instead.")

2021-08-02 10:40:28.146481: I tensorflow/core/platform/cpu\_feature\_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

69 texts collected.

Training on 2,506 character sequences.

2021-08-02 10:40:28.710370: I tensorflow/compiler/mlir/mlir\_graph\_optimization\_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2)

19/19 [==============================] - 6s 143ms/step - loss: 1.8994

####################

Temperature: 0.2

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Apache Streaming Streaming Station Stack

First Anti-Tatto Stack (A File State Stack Pack And Pussions

A Stack of Apache Stack

####################

Temperature: 0.5

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Cloud Dead Folk Streaming And Analance Art Past Flink

Into Apache Space Trades Channel Stack

Push Lake Station

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Temperature: 1.0

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Batt-Indunes Means Stgut

Sometimes time page

I real-posts, UIP Puming this reaction

Real-Timobitman with Apache and Flire

**Note installing on Mac:**

pip3 install git+git://github.com/minimaxir/textgenrnn.git

**tim.txt**

Apache NiFi 101:   Introduction and Best Practices

Cracking the Nut, Solving Edge AI with Apache Tools and Frameworks

FLANK Stack for Cloud Data Lakes

FLIP Stack for Cloud Data Lakes

Lightning Introduction to FLaNK

Pack Your Bags, We’re Going on a Data Journey!

Real-Time Streaming in Azure

Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp

Using the Mm FLaNK Stack for Edge AI (Flink, NiFi, Kafka, Kudu)

Utilizing Apache Kafka, Apache NiFi and MiNiFi for EdgeAI IoT at Scale

Real-Time Streaming in Any and All Clouds, Hybrid and Beyond

Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)

Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp

Hail Hydrate! From Stream to Lake with Pulsar and Friends

Continuous SQL with Kafka and Flink

FLiP Stack for Cloud Data Lakes

BUILDING EVENT STREAMING MICROSERVICES WITH NiFI Stateless AND APACHE PULSAR

CLOUD NATIVE STREAMING

USING REAL\_TIME DATA FEEDS

IOT STREAMING WITH MQTT, MINIFI AND PULSAR

BUILDING REAL\_TIME WEB APPLICATIONS WITH WEBSOCKETS AND PULSAR

KAFKA STREAM PROCESSING WITH SQL

CODELESS PIPELINES WITH KAFKA AND PULSAR

BUILD A REAL\_TIME PIPELINE NOW WITH PULSAR FUNCTIONS

Cloud Enterprise Data Platforms

Hybrid Cloud

Streaming with Flink, Kafka, NiFi

AI at the Edge with Microcontrollers and Small Devices

Voice Data In Queries

Event Handler as a Service (Automatic Kafka Message Reading)

More Powerful Parameter Based Modular Streaming

Cloud First For Big Data

Log Handling Moves to MiNiFi

Full AI At The Edge with Deployable Models

More Powerful Edge TPU/GPU/VPU

Kafka is everywhere

Open Source UI Driven Event Engines

FLaNK Stack gains popularity

FLINK Everywhere

Real-Time Stock Processing

Edge to AI:  Analytics from the Edge

Utilizing Apache NiFi for IoT

Let's Build A Simple Ingest To Cloud Datawarehouse with Low Code

Learning the Basics of Apache NiFi for IoT

Introduction to Flank Stack

Introduction to Flip Stack

Introduction to Pulsar

Apache Deep Learning 101

Big Data DevOps

Automating Social Media

Accessing Feeds from Etherdelta on Trades

Vision Thing

Deep Dive into Apache NiFi

Apache NiFi : Ingesting Enterprise Data at Scale

Continous SQL with Pulsar and Flink

Apache NiFi Deep Dive 300

Smart Transit:  Real-time Transit Information with FliP

Build in the Cloud

Streaming SQL and Data Flow

Real-Time Streaming Pipelines with FLaNK

Real-Time Streaming Pipelines with FLiP

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Next-Gen Apache NiFi

Ask the Experts

Hello, NiFi

Using Apache MXNet in Production Deep Learning Streaming Pipelines

From Stream to Lake