- Limitations of lambda (max file upload size)(01:07:03 - 01:09:00) - How to Schedule & Automatically Run Python Code!

- Limitations of lambda (max file upload size)(01:07:03 - 01:09:00)
How to Schedule & Automatically Run Python Code!

The first 1000 people to use the link will get a free trial of Skillshare Premium Membership: https://skl.sh/keithgalli11201

In this video we learn various methods for how we can schedule and automatically run python code. We'll start by looking at cronjobs & windows task scheduler and then ...
The first 1000 people to use the link will get a free trial of Skillshare Premium Membership: https://skl.sh/keithgalli11201

In this video we learn various methods for how we can schedule and automatically run python code. We'll start by looking at cronjobs & windows task scheduler and then we will walk through running tasks in the cloud using AWS Lambda & Cloudwatch. The ultimate goal of this video is to learn how we can automatically generate & send an email with an analytics report every day.

There are methods highlighted in this video that will work on Mac, Linux, & Windows.

~ GitHub resources ~
Link to source code: https://github.com/KeithGalli/scheduling-code
Link to analytics report code: https://github.com/KeithGalli/generate-analytics-report/tree/send_email

~ Relevant videos ~
How to generate an analytics report in python: https://youtu.be/UmN2_R4KEg8
How to send an email with python (@coreyms ): https://youtu.be/JRCJ6RtE3xU

~ Articles mentioned ~
AWS Lambda memory limits: https://hackernoon.com/exploring-the-aws-lambda-deployment-limits-9a8384b0bec3
Downloading python linux libraries on Windows: https://medium.com/@korniichuk/lambda-with-pandas-fd81aa2ff25e

~ Other resources ~
Python email library docs: https://docs.python.org/3.8/library/email.examples.html
AWS Cron info (scheduling): https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/ScheduledEvents.html
Lambda package setup: https://docs.aws.amazon.com/lambda/latest/dg/python-package.html

Thank you to Skillshare for sponsoring this video!

-------------------------
Video timeline!
0:00 - What we’ll be doing in this video
0:56 - Check out Skillshare! (sponsored)
1:56 - How can we automate scripts? Overview of local, cloud, and serverless methods
5:18 - Simple example of local script automation w/ cronjobs & windows task scheduler
18:32 - How to schedule code on a cloud machine (use cronjobs)
18:51 - Simple example of cloud script automation w/ AWS Lambda & Cloudwatch
27:09 - Schedule & automate sending an email locally
45:12 - Schedule & automate sending an email on the cloud w/ Lambda & Cloudwatch
50:18 - Installing python packages in a serverless environment (zip uploads)
55:50 - Generate & schedule sending analytics reports (locally)
1:02:45 - Generate & schedule sending analytics reports in AWS Lambda
1:07:03 - Limitations of lambda (max file upload size)
1:09:00 - Generate & schedule sending analytics reports in AWS Lambda
1:18:32 - Final thoughts & video recap!

-------------------------
Follow me on social media!
Instagram | https://www.instagram.com/keithgalli/
Twitter |

-------------------------
If you are curious to learn how I make my tutorials, check out this video: https://youtu.be/LEO4igyXbLs

Practice your Python Pandas data science skills with problems on StrataScratch!
https://stratascratch.com/?via=keith

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*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

#Keith Galli #python #programming #python 3 #data science #data analysis #python programming #crontab #cron job #cron tab #cron #analytics report #schedule code #schedule scripts #automate code #automate scripts #schedule code python #automating code #aws lambda #cloudwatch #cronjobs #scheduling code #mac #linux #windows #task scheduler #windows task scheduler #coding projects #data science projects #wsl #python 3.8 #serverless #run code in cloud #cloud #server #microsoft azure #aws
- What we’ll be doing in this video - How to Schedule & Automatically Run Python Code!

- What we’ll be doing in this video

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:00:00 - 00:00:56
- Check out Skillshare! (sponsored) - How to Schedule & Automatically Run Python Code!

- Check out Skillshare! (sponsored)

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:00:56 - 00:01:56
).hours.at("").do(func). but this is not working. - How to Schedule & Automatically Run Python Code!

).hours.at("").do(func). but this is not working.

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:01:00 - 01:20:23
- How can we automate scripts? Overview of local, cloud, and serverless methods - How to Schedule & Automatically Run Python Code!

- How can we automate scripts? Overview of local, cloud, and serverless methods

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:01:56 - 00:05:18
- Simple example of local script automation w/ cronjobs & windows task scheduler - How to Schedule & Automatically Run Python Code!

- Simple example of local script automation w/ cronjobs & windows task scheduler

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:05:18 - 00:18:32
- How to schedule code on a cloud machine (use cronjobs) - How to Schedule & Automatically Run Python Code!

- How to schedule code on a cloud machine (use cronjobs)

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:18:32 - 00:18:51
- Simple example of cloud script automation w/ AWS Lambda & Cloudwatch - How to Schedule & Automatically Run Python Code!

- Simple example of cloud script automation w/ AWS Lambda & Cloudwatch

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:18:51 - 00:27:09
- Schedule & automate sending an email locally - How to Schedule & Automatically Run Python Code!

- Schedule & automate sending an email locally

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:27:09 - 00:45:12
- Schedule & automate sending an email on the cloud w/ Lambda & Cloudwatch - How to Schedule & Automatically Run Python Code!

- Schedule & automate sending an email on the cloud w/ Lambda & Cloudwatch

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:45:12 - 00:50:18
- Installing python packages in a serverless environment (zip uploads) - How to Schedule & Automatically Run Python Code!

- Installing python packages in a serverless environment (zip uploads)

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:50:18 - 00:55:50
- Generate & schedule sending analytics reports (locally) - How to Schedule & Automatically Run Python Code!

- Generate & schedule sending analytics reports (locally)

How to Schedule & Automatically Run Python Code!
2020年11月27日 
00:55:50 - 01:02:45
- Limitations of lambda (max file upload size) - How to Schedule & Automatically Run Python Code!

- Limitations of lambda (max file upload size)

How to Schedule & Automatically Run Python Code!
2020年11月27日 
01:07:03 - 01:09:00
- Generate & schedule sending analytics reports in AWS Lambda - How to Schedule & Automatically Run Python Code!

- Generate & schedule sending analytics reports in AWS Lambda

How to Schedule & Automatically Run Python Code!
2020年11月27日 
01:09:00 - 01:18:32
- Final thoughts & video recap! - How to Schedule & Automatically Run Python Code!

- Final thoughts & video recap!

How to Schedule & Automatically Run Python Code!
2020年11月27日 
01:18:32 - 01:20:23

Keith Galli

※本サイトに掲載されているチャンネル情報や動画情報はYouTube公式のAPIを使って取得・表示しています。

Timetable

動画タイムテーブル

動画数:87件

- Intro & Setup - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Intro & Setup

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:00:00 - 00:02:14
great video! however, regarding the usage of the terminal to create directories etc at  , can anyone recommend some youtube videos or sources to get more familiar with it? thanks a bunch! good luck getting good at pandas everybody :) - Solving 100 Python Pandas Problems! (from easy to very difficult)

great video! however, regarding the usage of the terminal to create directories etc at , can anyone recommend some youtube videos or sources to get more familiar with it? thanks a bunch! good luck getting good at pandas everybody :)

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日  @realzeejay 様 
00:00:59 - 05:20:18
- Problems (1-3) Initial pandas setup - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Problems (1-3) Initial pandas setup

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:02:14 - 00:04:42
- Problems (4-10) DataFrame operations - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Problems (4-10) DataFrame operations

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:04:42 - 00:04:52
- 4) Create a dataframe from dictionary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 4) Create a dataframe from dictionary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:04:52 - 00:05:24
- 5) Display dataframe summary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 5) Display dataframe summary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:05:24 - 00:05:41
- 6) First 3 rows of the dataframe - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 6) First 3 rows of the dataframe

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:05:41 - 00:06:02
- 7) Select ‘animal’ and ‘age’ columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 7) Select ‘animal’ and ‘age’ columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:06:02 - 00:07:42
- 8) Data in specific rows and columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 8) Data in specific rows and columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:07:42 - 00:09:06
- 9) Rows with visits greater than 3 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 9) Rows with visits greater than 3

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:09:06 - 00:09:57
- 10) Rows with NaN in age - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 10) Rows with NaN in age

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:09:57 - 00:10:56
- 11) Cats younger than 3 years - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 11) Cats younger than 3 years

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:10:56 - 00:11:35
- 12) Age between 2 and 4 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 12) Age between 2 and 4

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:11:35 - 00:12:45
- 13) Change age in row ‘f’ - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 13) Change age in row ‘f’

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:12:45 - 00:15:56
- 14) Sum of all visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 14) Sum of all visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:15:56 - 00:16:41
- 15) Average age by animal - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 15) Average age by animal

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:16:41 - 00:20:21
I do this a lot, by passing a dict to the agg function after grouping (it allows you to asign multiple operators to several cols at once). Eg df.groupby(“animal”).agg({“age”:”mean”}) - Solving 100 Python Pandas Problems! (from easy to very difficult)

I do this a lot, by passing a dict to the agg function after grouping (it allows you to asign multiple operators to several cols at once). Eg df.groupby(“animal”).agg({“age”:”mean”})

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日  @AgustinGonzalez-tz3yr 様 
00:19:30 - 05:20:18
- 16) Modify and revert rows - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 16) Modify and revert rows

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:20:21 - 00:24:06
- 17) Count by animal type - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 17) Count by animal type

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:24:06 - 00:25:28
- Quick review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Quick review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:25:28 - 00:26:17
- 18) Sort by age and visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 18) Sort by age and visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:26:17 - 00:28:07
- 19) Convert 'priority' to boolean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 19) Convert 'priority' to boolean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:28:07 - 00:29:42
- 20) Replace 'snake' with 'python' - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 20) Replace 'snake' with 'python'

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:29:42 - 00:30:53
- 21) Mean age by animal and visits - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 21) Mean age by animal and visits

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:30:53 - 00:33:49
- Advanced DataFrame techniques - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Advanced DataFrame techniques

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:33:49 - 00:33:57
- 22) Filter duplicate integers - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 22) Filter duplicate integers

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:33:57 - 00:43:18
- 23) Subtract row mean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 23) Subtract row mean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:43:18 - 00:45:42
- 24) Column with smallest sum - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 24) Column with smallest sum

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:45:42 - 00:50:39
- 25) Count unique rows - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 25) Count unique rows

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:50:39 - 00:53:17
- 26) Column with third NaN - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 26) Column with third NaN

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
00:53:17 - 01:10:27
- Solution review for 26 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Solution review for 26

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:10:27 - 01:17:13
- 27) Sum of top three values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 27) Sum of top three values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:17:13 - 01:24:01
- 28) Sum by column condition - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 28) Sum by column condition

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:24:01 - 01:40:11
- Recent problem review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Recent problem review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:40:11 - 01:42:53
- 29) Count differences since last zero - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 29) Count differences since last zero

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:42:53 - 01:56:19
- 30) Locate largest values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 30) Locate largest values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
01:56:19 - 02:08:38
- 31) Replace negatives with mean - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 31) Replace negatives with mean

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:08:38 - 02:17:43
- 32) Rolling mean over groups - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 32) Rolling mean over groups

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:17:43 - 02:23:10
- Series and DatetimeIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Series and DatetimeIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:23:10 - 02:23:12
- 33) DatetimeIndex for 2015 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 33) DatetimeIndex for 2015

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:23:12 - 02:27:56
- 34) Sum values on Wednesdays - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 34) Sum values on Wednesdays

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:27:56 - 02:45:04
- 35) Monthly mean values - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 35) Monthly mean values

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:45:04 - 02:46:16
- 36) Best value in four-month groups - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 36) Best value in four-month groups

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:46:16 - 02:50:26
- 37) DatetimeIndex of third Thursdays - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 37) DatetimeIndex of third Thursdays

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:50:26 - 02:59:03
- Cleaning Data - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Cleaning Data

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:59:03 - 02:59:40
- 38) Fill missing FlightNumber - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 38) Fill missing FlightNumber

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
02:59:40 - 03:02:45
- 39) Split column by delimiter - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 39) Split column by delimiter

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:02:45 - 03:06:47
- 40) Fix city name capitalization - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 40) Fix city name capitalization

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:06:47 - 03:08:30
- 41) Reattach columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 41) Reattach columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:08:30 - 03:13:11
- 42) Fix airline name punctuation - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 42) Fix airline name punctuation

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:13:11 - 03:17:45
- 43) Expand RecentDelays into columns - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 43) Expand RecentDelays into columns

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:17:45 - 03:27:31
- MultiIndexes in Pandas - Solving 100 Python Pandas Problems! (from easy to very difficult)

- MultiIndexes in Pandas

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:27:31 - 03:27:34
- 44) Construct a MultiIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 44) Construct a MultiIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:27:34 - 03:30:37
- Solution review - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Solution review

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:30:37 - 03:32:44
- 45) Lexicographically sorted check - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 45) Lexicographically sorted check

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:32:44 - 03:32:58
- 46) Select specific MultiIndex labels - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 46) Select specific MultiIndex labels

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:32:58 - 03:34:23
- 47) Slice Series with MultiIndex - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 47) Slice Series with MultiIndex

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:34:23 - 03:35:24
- 48) Sum by first level - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 48) Sum by first level

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:35:24 - 03:37:47
- 49) Alternative sum method - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 49) Alternative sum method

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:37:47 - 03:40:08
- Additional solution insights - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Additional solution insights

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:40:08 - 03:41:22
- 50) Swap MultiIndex levels - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 50) Swap MultiIndex levels

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:41:22 - 03:45:27
- Minesweeper problems - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Minesweeper problems

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:45:27 - 03:45:44
- 51) Generate coordinate grid - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 51) Generate coordinate grid

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
03:45:44 - 04:00:28
- 52) Add 'safe' or 'mine' column - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 52) Add 'safe' or 'mine' column

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:00:28 - 04:03:04
- 53) Count adjacent mines - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 53) Count adjacent mines

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:03:04 - 04:27:33
- Review solution to 53 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Review solution to 53

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:27:33 - 04:33:02
- Skipped problems 54 & 55 - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Skipped problems 54 & 55

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:33:02 - 04:33:11
- Plotting - Solving 100 Python Pandas Problems! (from easy to very difficult)

- Plotting

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:33:11 - 04:33:12
- 56) Scatter plot with black x markers - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 56) Scatter plot with black x markers

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:33:12 - 04:41:26
- 57) Plot four data types - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 57) Plot four data types

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:41:26 - 04:52:50
- 58) Overlay multiple graphs - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 58) Overlay multiple graphs

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
04:52:50 - 05:03:11
- 59) Hourly stock data summary - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 59) Hourly stock data summary

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
05:03:11 - 05:14:12
- 60) Candlestick plot - Solving 100 Python Pandas Problems! (from easy to very difficult)

- 60) Candlestick plot

Solving 100 Python Pandas Problems! (from easy to very difficult)
2024年04月14日 
05:14:12 - 05:20:18
- Intro & Live Stream Overview - Ask me anything! (data science, LLMs, landing a job, and more)

- Intro & Live Stream Overview

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:00:00 - 00:04:58
- How over saturated is the data science job market and will things improve in your opinion? - Ask me anything! (data science, LLMs, landing a job, and more)

- How over saturated is the data science job market and will things improve in your opinion?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:04:58 - 00:07:26
- How much maths is needed to get a data science job? - Ask me anything! (data science, LLMs, landing a job, and more)

- How much maths is needed to get a data science job?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:07:26 - 00:09:55
- Can you share a basic roadmap to learn generative AI and LLMs? - Ask me anything! (data science, LLMs, landing a job, and more)

- Can you share a basic roadmap to learn generative AI and LLMs?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:09:55 - 00:13:08
- What future-proof tech career to should someone focus on who’s looking to change career? - Ask me anything! (data science, LLMs, landing a job, and more)

- What future-proof tech career to should someone focus on who’s looking to change career?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:13:08 - 00:16:52
- Is data structures & algorithms (dsa) necessary to get a job in data science? - Ask me anything! (data science, LLMs, landing a job, and more)

- Is data structures & algorithms (dsa) necessary to get a job in data science?

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:16:52 - 00:19:17
- How to get good at data structures and algorithms? - Ask me anything! (data science, LLMs, landing a job, and more)

- How to get good at data structures and algorithms?

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2024年04月07日 
00:19:17 - 00:22:20
- Why don’t you make videos regularly now? - Ask me anything! (data science, LLMs, landing a job, and more)

- Why don’t you make videos regularly now?

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2024年04月07日 
00:22:20 - 00:24:18
- How much do you need to know for entry-level roles / college internships? - Ask me anything! (data science, LLMs, landing a job, and more)

- How much do you need to know for entry-level roles / college internships?

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2024年04月07日 
00:24:18 - 00:27:02
- How important is domain knowledge for data science? - Ask me anything! (data science, LLMs, landing a job, and more)

- How important is domain knowledge for data science?

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2024年04月07日 
00:27:02 - 00:29:29
- Amazon’s AI-based ‘just walk out’ retail checkout tech controversy thoughts - Ask me anything! (data science, LLMs, landing a job, and more)

- Amazon’s AI-based ‘just walk out’ retail checkout tech controversy thoughts

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
00:29:29 - 00:32:30
- Any good data projects to increase visibility to companies? - Ask me anything! (data science, LLMs, landing a job, and more)

- Any good data projects to increase visibility to companies?

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2024年04月07日 
00:32:30 - 00:36:05
- Do you think we should all learn vector databases? - Ask me anything! (data science, LLMs, landing a job, and more)

- Do you think we should all learn vector databases?

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2024年04月07日 
00:36:05 - 00:39:10
- Is webscraping illegal? what can I do and not do? - Ask me anything! (data science, LLMs, landing a job, and more)

- Is webscraping illegal? what can I do and not do?

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2024年04月07日 
00:39:10 - 00:43:14
- What are you working on at the moment? - Ask me anything! (data science, LLMs, landing a job, and more)

- What are you working on at the moment?

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2024年04月07日 
00:43:14 - 00:45:25
- How can I turn a financial database I’m building into an interesting portfolio project to showcase work? - Ask me anything! (data science, LLMs, landing a job, and more)

- How can I turn a financial database I’m building into an interesting portfolio project to showcase work?

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2024年04月07日 
00:45:25 - 00:49:23
- What advice do you have for data scientists who want to get into freelance/consulting? - Ask me anything! (data science, LLMs, landing a job, and more)

- What advice do you have for data scientists who want to get into freelance/consulting?

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2024年04月07日 
00:49:23 - 00:55:15
- What are important skills for DS beyond ML & AI? - Ask me anything! (data science, LLMs, landing a job, and more)

- What are important skills for DS beyond ML & AI?

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2024年04月07日 
00:55:15 - 00:59:42
- Do I need to become a full-stack programmer to have success in this field? - Ask me anything! (data science, LLMs, landing a job, and more)

- Do I need to become a full-stack programmer to have success in this field?

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2024年04月07日 
00:59:42 - 01:02:31
- If you weren’t allowed to do programming or create content, what would you do? - Ask me anything! (data science, LLMs, landing a job, and more)

- If you weren’t allowed to do programming or create content, what would you do?

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2024年04月07日 
01:02:31 - 01:03:39
- How did you achieve your advanced height? Asking for a friend. - Ask me anything! (data science, LLMs, landing a job, and more)

- How did you achieve your advanced height? Asking for a friend.

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2024年04月07日 
01:03:39 - 01:04:23
- Final thoughts. Thanks for coming!-------------------------Follow me on social media!Instagram | https://www.instagram.com/keithgalli/Twitter | https://twitter.com/keithgalliTikTok | https://tiktok.com/@keithgalli-------------------------Practice your Python Pandas data science skills with problems on StrataScratch!https://stratascratch.com/?via=keithJoin the Python Army to get access to perks!YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/joinPatreon - https://www.patreon.com/keithgalli*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links. - Ask me anything! (data science, LLMs, landing a job, and more)

- Final thoughts. Thanks for coming!-------------------------Follow me on social media!Instagram | https://www.instagram.com/keithgalli/Twitter | https://twitter.com/keithgalliTikTok | https://tiktok.com/@keithgalli-------------------------Practice your Python Pandas data science skills with problems on StrataScratch!https://stratascratch.com/?via=keithJoin the Python Army to get access to perks!YouTube - https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw/joinPatreon - https://www.patreon.com/keithgalli*I use affiliate links on the products that I recommend. I may earn a purchase commission or a referral bonus from the usage of these links.

Ask me anything! (data science, LLMs, landing a job, and more)
2024年04月07日 
01:04:23 - 01:05:26
- Video Overview & Reference Material - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Video Overview & Reference Material

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:00:00 - 00:03:05
-  Data & Code Setup - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Data & Code Setup

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:03:05 - 00:05:04
- Task #0: Configure LLM to use with Python (OpenAI API) - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #0: Configure LLM to use with Python (OpenAI API)

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:05:04 - 00:20:10
- Task #0 (continued): LLM Configuration with Open-Source Model (LLama 2 via Ollama) - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #0 (continued): LLM Configuration with Open-Source Model (LLama 2 via Ollama)

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:20:10 - 00:27:39
- Task #1: Use LLM to Parse Simple Sentence Examples - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #1: Use LLM to Parse Simple Sentence Examples

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:27:39 - 00:41:22
- Sub-task #1: Convert string to Python Object - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Sub-task #1: Convert string to Python Object

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:41:22 - 00:44:29
- Task #1 (continued): Use Open-Source LLM to Parse Sentence Examples w/ LangChain - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #1 (continued): Use Open-Source LLM to Parse Sentence Examples w/ LangChain

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:44:29 - 00:56:24
- Quick note on a benefit of using LangChain (easily switching between models) - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Quick note on a benefit of using LangChain (easily switching between models)

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:56:24 - 00:58:06
- Task #2 (warmup): Grab Apprenticeship Agreement rows from Dataframe - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #2 (warmup): Grab Apprenticeship Agreement rows from Dataframe

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
00:58:06 - 01:06:22
- Task #2: Connect Pages that Belong to the Same Documents - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #2: Connect Pages that Belong to the Same Documents

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
01:06:22 - 01:56:36
Fantastic real world problem as a lot of your other videos. I've got to say that all models on Ollama absolutely stink in comparison to OpenAI. However I have been using a preprocessing text function I created for using in a news article project I'm working on using Spacy. I have been able to pass the transcription_text's through my function with some minor tweaking and have been able to recreate what the LLM's are doing just through code, by using the doc.ents functionality. Only  through the video at the moment and perhaps you use something similar later on, but  Spacy has been a bit of a godsend if you don't/can't pay for OpenAI - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

Fantastic real world problem as a lot of your other videos. I've got to say that all models on Ollama absolutely stink in comparison to OpenAI. However I have been using a preprocessing text function I created for using in a news article project I'm working on using Spacy. I have been able to pass the transcription_text's through my function with some minor tweaking and have been able to recreate what the LLM's are doing just through code, by using the doc.ents functionality. Only through the video at the moment and perhaps you use something similar later on, but Spacy has been a bit of a godsend if you don't/can't pay for OpenAI

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日  @MaxwellSmi41483 様 
01:27:00 - 02:39:33
- Task #3: Parse out values from merged documents - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #3: Parse out values from merged documents

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
01:56:36 - 02:12:44
- Task #4 (setup): Analyze Results - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #4 (setup): Analyze Results

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:12:44 - 02:17:52
- Fixing up our results from task #3 quickly - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Fixing up our results from task #3 quickly

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:17:52 - 02:20:41
- Task #4: Find the average age of apprentices in our merged contract documents - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Task #4: Find the average age of apprentices in our merged contract documents

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:20:41 - 02:30:59
- Other analysis, wlho had the most apprentices? - Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)

- Other analysis, wlho had the most apprentices?

Solving Real-World Data Science Problems with LLMs! (Historical Document Analysis)
2024年03月21日 
02:30:59 - 02:39:33