BIG ANNOUNCEMENT: I'm beyond excited to announce that in 5 days, I'm launching my brand new course- The #Python for Machine Learning & API's Course.

This course will transform your #career.

Here's what's inside... 🧵

#datascience #course Image
This launch marks the culmination of 2 years of research...

It covers The 6 Top #Python libraries for machine learning and production:
1. #Pycaret: Low-code machine learning Image
2. #ScikitLearn: The premier ML toolkit in Python Image
3. #H2O: Blazing speed + AutoML Image
4. #MLFlow: Easy model lifecycle management Image
5. #FastAPI: Incredibly fast + easy APIs in python Image
6. #Streamlit: Simplified data science web apps Image
Ready to learn more AND advance your career with Python?

Then you can't miss this event.

$400 in giveaways that everyone gets for attending live!
What's the next step?

Just join my course waitlist + live launch event here.

I'm super excited!! 😀

👉Register Here: learn.business-science.io/python-ml-apis… Image

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More from @mdancho84

Dec 12
Some people really like Data Cleaning. I don't.

It takes me away from analyzing data. The fun part.

So I made an AI Agent to help. Image
The AI Agent contains 4 steps:

1. Create data cleaner code
2. Execute data cleaner code
3. If problem, fix code
4. Once fixed, explain code

Here's how it works:
1. In the first step, the AI analyzes an incoming data set.

Based on the features and statistics of the dataset, it creates code to perform a custom data cleaning.

Key skill: Python Code Generation Image
Read 11 tweets
Nov 16
Python has powerful time series libraries.

Case in point: skforecast

Let me explain: Image
Skforecast is a Python library for time series forecasting using machine learning models.

Skforecast works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others. Image
skforecast shines with probabilistic forecasting.

When trying to anticipate future values, most forecasting models try to predict what will be the most likely value.

This is called point forecasting.
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Nov 15
My favorite R package for ultra-fast exploratory analysis: Image
The R package is called correlationfunnel.

Yes, I built it.
What correlationfunnel does is:

* Speeds Up Exploratory Data Analysis

* Improves Feature Selection

* Gets You To Business Insights Faster Image
Read 6 tweets
Nov 14
The best beginner book on time series?

FPP: Forecasting Principles and Practice

Let's dive in: Image
Some may consider FPP the bible of time series.

I agree.

Start with FPP Version 2 or 3, and you won't go wrong.

This is what I like:
1. Time Series Visualizations

There's no better intuition for time series than a visualization.

- Time Plots
- Seasonal Plots
- ACF Plots

All are absolutely critical to understanding time series patterns. Image
Read 9 tweets
Nov 12
BEAST: A Bayesian Ensemble Algorithm for Change-Point Detection and Time Series Decomposition in R

Let's explore: Image
1. What is BEAST?

BEAST stands for Bayesian Estimator of Abrupt change, Seasonality, and Trend.

But what does that mean?
According to the authors, BEAST is a fast, generic Bayesian model averaging algorithm to decompose time series or 1D sequential data into individual components, such as abrupt changes, trends, and periodic/seasonal variations
Read 8 tweets
Nov 11
I used to struggle with working with Time Series.

After 10 years, I mastered it.

Then I spent 3 years making this R package so you can too: Image
The R package is timetk. I built it to make your life easier when working with Time Series:

- Plotting (Visualization)
- Data Wrangling
- Correlation
- Seasonality
- Imputation
- Outliers (Anomalies)
- Feature engineering
- Cross Validation
I'll focus on Time Series Plotting today.

1. Plotting Time Series: Use plot_time_series() Image
Read 12 tweets

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