mikulskibartosz.name

GENERAL
META
HTML
LINK ANALYSIS
SERVER
IP

Mikulskibartosz.name receives any estimated 153 unique visitors and 271 unique page views per day. Revenue gained from these much visits may be $0 per day from various advertising sources. The estimated worth of site is $191. Alexa global rank is 3,570,206. Maximum no. of users comes from UNITED STATES. Rank in UNITED STATES is 2,467,778.

Amazon.com, Inc. is ISP, hosted on IP 13.226.217.11 in Country United States.

Website Age n/a
Alexa Rank no-data
Country United States
IP Address 13.226.217.11

META INFORMATION

Title

Bartosz Mikulski - big data consultant | Bartosz Mikulski

Description

Data Craft - making data pipelines trustworthy

Keywords

Content Type

utf-8

No	Meta Name	Value
1	viewport	width=device-width, initial-scale=1, shrink-to-fit=no

google ads

GENERAL HTML INFORMATION

Type	Status
HTML 5
Responsive Website

HTML SIZE INFORMATION

Text / Code Ratio 11.01 %

mikulskibartosz.name has a website text/code ratio of 11.01 %. Search engine crawlers tend to not pick up pages with inadequate content.

IMPORTANT HTML TAGS AND COUNTS

Titles

H11
H218
H30
H415
H50
H60

No	Text
1	Bartosz mikulski

No	Text
1	Featured
2	How to train a reinforcement learning agent using tensorflow agents
3	How to deal with underf**ing and overf**ing in deep learning
4	How to split a list inside a dataframe cell into rows in pandas
5	Monte carlo simulation in python
6	All stories
7	The problem with software testing in data engineering
8	How does kafka connect work?
9	Why my airflow tasks got stuck in "no_status" and how ı fixed it
10	What is kafka log compaction, and how does it work?
11	How does a kafka cluster work?
12	Athena performance tips explained
13	Data flow - what functional programming and unix philosophy can teach us about data streaming
14	Aws ıam roles and policies explained
15	How to be happy at work - lessons learned from "career superpowers" book
16	How to send metrics to aws cloudwatch from custom python code
17	How to unit test pyspark
18	How to speed up a pyspark job

No	Text
1	The reinforcement learning loop with tensorflow agents
2	The lessons learned from andrew ng’s online course
3	Step by step instructions to "explode" a list into dataframe rows.
4	How to make business decisions using the monte carlo simulation?
5	What if we found a bug in our data pipelines? what if that bug were easy to fix, but it would require a lot of time spent backfilling the data?...
6	ın this article, ı am going to describe the internals of kafka connect, explain how it uses the sink and source connectors, and how it tracks the offsets of the...
7	A story about debugging an airflow dag that was not starting tasks
8	How the log compaction is implemented in apache kafka and how to configure it properly
9	What is the difference between a leader and a replica broker? what is the cluster controller? how is the controller elected?
10	How to use query execution plans to speed up athena queries
11	What does stream processing have in common with functional programming and unix?
12	ın this article, ı am going to explain the essential parts of ıam and describe how to grant permissions to your users or aws lambda functions you wrote.
13	ın this article, ı share the lessons ı learned from james whittaker’s book “career superpowers: succeeding on purpose.”
14	Recently, ı came across an interesting problem: how to speed up the feedback loop while maintaining a pyspark dag. of course, ı could just run the spark job and look...
15	ı had a spark job that occasionally was running extremely slow. on a typical day, spark needed around one hour to finish it, but sometimes it required over four hours....

Text Styling

STRONG0
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CITE0

LINK ANALYSIS

Total Link Count: 104

Internal Link Count : 99

No	Text	Type
1	Consulting	text
2	Speaker	text
3	Bartosz Mikulski	text
4	How to train a Reinforcement Learning Agent using Tensorflow Agents	text
5	The reinforcement learning loop with Tensorflow Agents	text
6	Bartosz Mikulski	text
7	#Reinforcement learning	text
8	#TensorFlow	text
9	How to deal with underf**ing and overf**ing in deep learning	text
10	The lessons learned from Andrew Ng’s online course	text
11	Bartosz Mikulski	text
12	#Deep learning	text
13	How to split a list inside a Dataframe cell into rows in Pandas	text
14	Step by step instructions to "explode" a list into DataFrame rows.	text
15	Bartosz Mikulski	text
16	#Data Science	text
17	Monte Carlo simulation in Python	text
18	How to make business decisions using the Monte Carlo simulation?	text
19	Bartosz Mikulski	text
20	#Data Science	text
21	The problem with software testing in data engineering	text
22	What if we found a bug in our data pipelines? What if that bug were easy to fix, but it would require a lot of time spent backfilling the data?...	text
23	Bartosz Mikulski	text
24	#Data Engineering	text
25	#Software Craft	text
26	How does Kafka Connect work?	text
27	In this article, I am going to describe the internals of Kafka Connect, explain how it uses the Sink and Source Connectors, and how it tracks the offsets of the...	text
28	Bartosz Mikulski	text
29	#Apache Kafka	text
30	#Data Engineering	text
31	Why my Airflow tasks got stuck in "no_status" and how I fixed it	text
32	A story about debugging an Airflow DAG that was not starting tasks	text
33	Bartosz Mikulski	text
34	#Airflow	text
35	#Data Engineering	text
36	What is Kafka log compaction, and how does it work?	text
37	How the log compaction is implemented in Apache Kafka and how to configure it properly	text
38	Bartosz Mikulski	text
39	#Apache Kafka	text
40	#Data Engineering	text
41	How does a Kafka Cluster work?	text
42	What is the difference between a leader and a replica broker? What is the cluster controller? How is the controller elected?	text
43	Bartosz Mikulski	text
44	#Apache Kafka	text
45	#Data engineering	text
46	Athena performance tips explained	text
47	How to use query execution plans to speed up Athena queries	text
48	Bartosz Mikulski	text
49	#AWS	text
50	#Data Engineering	text

External Link Count : 5

No	Text	Type
1	-	empty
2	-	empty
3	-	empty
4	-	empty
5	Mediumish Jekyll Theme	text

Nofollow Link Count : 0

Title Link Count : 0

WEBSITE SERVER INFORMATION

Service Provider (ISP)
Amazon.com, Inc.
Hosted IP Address
13.226.217.11
Hosted Country
United States
Host Region
California , Los Angeles
Latitude and Longitude
34.0522 : -118.244

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