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🔥 Matt Dancho (Business Science) 🔥 Profile picture
@mdancho84
May 20, 2023 • 10 tweets • 5 min read • Read on X
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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

🔥 Matt Dancho (Business Science) 🔥 Profile picture
Apr 2
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. Image
Read 9 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Mar 25
Becoming an AI data scientist has levels to it.

Here's a complete roadmap: Image
Becoming an AI data scientist is a journey with multiple levels, each requiring specific tools and skills.

I’ve outlined a progression of levels with relevant skills and tools:
Level 1: Foundations of Data Science

- Python: Core programming language for data science (e.g., variables, loops, functions).
- Pandas: Data manipulation and analysis (e.g., DataFrames, cleaning data).
- NumPy: Numerical computations (e.g., arrays, linear algebra basics).
-Plotly: Data visualization (e.g., plotting charts, exploring trends).
- SQL: Querying databases for data extraction.Image
Read 7 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Mar 24
Understanding P-Values is essential for improving regression models.

In 2 minutes, I'll crush your confusion.

Let's go: Image
1. The p-value:

A p-value in statistics is a measure used to assess the strength of the evidence against a null hypothesis. Image
2. Null Hypothesis (H₀):

The null hypothesis is the default position that there is no relationship between two measured phenomena or no association among groups. For example, under H₀, the regressor does not affect the outcome. Image
Read 13 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Mar 23
Data scientists are out.

The Generative AI Data Scientist is in.

Let me explain: Image
Companies are sitting on mountains of unstructured data.

PDF
Word docs
Meeting notes
Emails
Videos
Audio Transcripts

This is useful data. But it's unusable in its existing form. Image
The AI data scientist builds the systems to analyze information, gain business insights, and automates the process.

- Models the system
- Use AI to extract insights
- Drives predictive business insights

Want to become a Generative AI Data Scientist in 2025? Image
Read 5 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Mar 23
Correlation is the skill that has singlehandedly benefitted me the most in my career.

In 3 minutes I'll demolish your confusion (and share strengths and weaknesses you might be missing).

Let's go: Image
1. Correlation:

Correlation is a statistical measure that describes the extent to which two variables change together. It can indicate whether and how strongly pairs of variables are related. Image
2. Types of correlation:

Several types of correlation are used in statistics to measure the strength and direction of the relationship between variables. The three most common types are Pearson, Spearman Rank, and Kendall's Tau. We'll focus on Pearson since that is what I use 95% of the time.Image
Read 11 tweets
🔥 Matt Dancho (Business Science) 🔥 Profile picture
Mar 22
Data Science for Business.

The book that helped me connect the dots. Let's dive in: Image
1. CRISP Data Mining Process

The foundation for applying data science to business is the CRISP method.

This is a helpful framework for integrating data science with the business understanding. Image
2. Machine Learning Predictions as Probabilities

One of the most important part of machine learning is probability.

We can estimate the probability from machine learning predictions.

Once you get this, the next framework opens up: Image
Read 7 tweets

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