bun.bun.🐽
@DS_Bun_
Followers
18,922
Following
16,728
Media
4
Statuses
79,175
love #pugs , senior data scientist @datafying my tweet = data science, machine learning, ai, deep learning and pug as well.
Australia
Joined August 2014
Don't wanna be here?
Send us removal request.
Explore trending content on Musk Viewer
Jalisco
• 193846 Tweets
Janones
• 160407 Tweets
D-Day
• 108139 Tweets
Nikolas
• 90293 Tweets
ファンタジースプリングス
• 88987 Tweets
Star Wars
• 73616 Tweets
Boulos
• 65879 Tweets
Nvidia
• 52060 Tweets
Alvarez
• 50334 Tweets
Jim Crow
• 46144 Tweets
対象の3作品
• 30374 Tweets
#木村柾哉
• 29153 Tweets
コインor時短
• 28194 Tweets
Harriet
• 18941 Tweets
#すとーんずラブの日
• 17570 Tweets
Andorra
• 13949 Tweets
Ohtani
• 13011 Tweets
悪魔の日
• 10686 Tweets
Paul Skenes
• 10616 Tweets
César Maia
• 10330 Tweets
Pinned Tweet
IBM Product Manager Professional Certificate
👋 An Introduction
🤝 Foundations & Stakeholder Collaboration
📝 Initial Product Strategy and Plan
🚀 Developing and Delivering a New Product
🔄 Introduction to Agile Development and Scrum
🎓 Capstone Project
0
5
30
Data Science Fundamentals for Data Analysts
2
127
573
How to Deploy Machine Learning Models
3
118
545
Python Project for Data Science
1
119
530
31 Datasets For Your Next Data Science Project
7
98
393
How to Forecast Time Series Data Using Deep Learning
2
92
374
Data scientist’s guide to efficient coding in Python
2
77
371
Introduction to Machine Learning in Sports Analytics
3
66
355
Data scientist’s guide to efficient coding in Python
1
72
318
Linear programming with Python and Julia
3
65
271
From Jupyter Notebook to Deployment — A Straightforward Example
1
59
266
Simulating Traffic Flow in Python
1
68
264
Data scientist’s guide to efficient coding in Python
0
52
256
A Practical Guide to Linear Regression
0
70
253
Graph Machine Learning with Python Part 1: Basics, Metrics, and Algorithms
0
54
238
Data scientist’s guide to efficient coding in Python
0
56
218
t-SNE Machine Learning Algorithm — A Great Tool for Dimensionality Reduction in Python
2
53
212
Forecasting Models for Marketing Decisions
4
42
206
Bayesian Statistics Overview and your first Bayesian Linear Regression Model
1
56
209
Complete Machine Learning pipeline for NLP tasks
1
53
206
Complete Machine Learning pipeline for NLP tasks
1
71
205
How to Use Streamlit and Python to Build a Data Science App
1
38
186
Linear programming with Python and Julia
1
30
182
A Full End-to-End Deployment of a Machine Learning Algorithm into a Live Production Environment
0
43
170
Crime Location Analysis and Prediction Using Python and Machine Learning
0
39
149
Microsoft Azure Machine Learning
0
34
158
Complete Machine Learning pipeline for NLP tasks
1
34
127
Logistic Regression from First Principles in Python
0
36
119
Advancing into Analytics: From Excel to Python and R
1
15
110
Decision Tree Models in Python — Build, Visualize, Evaluate
0
34
115
Build a machine learning web app in Python
1
29
116
3 ways to deal with large datasets in Python
0
34
102
Data Visualization with R
1
28
97
Deep Learning with Python: Neural Networks (complete tutorial)
1
35
96
Build a machine learning web app in Python
0
22
100
A Practical Guide to Linear Regression
0
23
95
SHAP: Explain Any Machine Learning Model in Python
0
24
94
Complete Guide to Regressional Analysis Using Python
0
28
91
How to Analyze Football Event Data Using Python
0
29
87
Deep Learning with Python: Neural Networks (complete tutorial)
0
29
90
Git and GitHub basics for Data Scientists
0
27
83
Complete Machine Learning pipeline for NLP tasks
0
23
80
5 ways to Increase Statistical Power
0
15
73
Speech Recognition in Real-Time using Python
1
25
72
Deep Learning with Python: Neural Networks (complete tutorial)
0
21
72
A Complete Guide of How to Choose and Apply the Right Statistical Test in Python
0
20
67
Considerations for Deploying Machine Learning Models in Production
1
18
63
K-Means Clustering - An Explorable Explainer
0
18
66
Bayesian Inference and Markov Chain Monte Carlo Sampling in Python
0
11
65
Bayesian Statistics Overview and your first Bayesian Linear Regression Model
0
17
65
Logistic Regression from First Principles in Python
0
18
64
Considerations for Deploying Machine Learning Models in Production
0
19
64
Data scientist’s guide to efficient coding in Python
0
16
59
Random Forests Algorithm explained with a real-life example and some Python code
0
19
61
Understanding Python imports, __init__.py and pythonpath — once and for all
0
19
59
How to Analyze Football Event Data Using Python
0
19
58
Orchestrate a Data Science Project in Python With Prefect
0
15
56
Understanding Python imports, __init__.py and pythonpath — once and for all
0
13
58
How to Use Streamlit and Python to Build a Data Science App
0
14
58
Complete Guide to Regressional Analysis Using Python
0
7
57
30 Probability and Statistics Interview Questions for Data Scientists
0
15
55
How to create products that rely on machine learning
0
14
55
31 Datasets For Your Next Data Science Project
2
20
55
Deep Learning: Convolutional Neural Networks in Python. Use CNNs for Image Recognition, Natural Language Processing (NLP) +More! For Data Science, Machine Learning, and AI.
#DataScience
#MachineLearning
#ad
0
29
51
Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines
0
12
52
Fundamentals of Data Analysis
1
13
54
Five Regression Python Modules That Every Data Scientist Must Know
0
22
54
How to Develop Interpretable Time Series Forecasts with Deep Learning
0
8
52
3 ways to deal with large datasets in Python
1
14
49
Statistics in Python — Using Chi-Square for Feature Selection
0
14
50
7 Techniques to Handle Multicollinearity that Every Data Scientist Should Know
1
7
49
18 Data Science Project Ideas for Beginners
0
11
48
Data Scientist Toolkit — Introduction to SQL
0
7
50
Introduction to Anomaly Detection in Python with PyCaret
0
10
49
Machine Learning: Theory and Hands-on Practice with Python
1
14
47
Build a machine learning web app in Python
0
11
47
Introduction to Big Data
0
9
44
How to Compare Two or More Distributions
0
9
46
Complete Guide to Regressional Analysis Using Python
0
16
46
Complete Machine Learning pipeline for NLP tasks
0
14
46
t-SNE Machine Learning Algorithm — A Great Tool for Dimensionality Reduction in Python
0
16
47
Decision Tree Models in Python — Build, Visualize, Evaluate
0
18
45
Machine Learning Toolbox: This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
0
21
42
Introduction to TensorFlow in R. Learn how to use TensorFlow, a state-of-the-art machine learning framework that specializes in the ability to develop deep learning neural networks
#rstats
#tensorflow
#machinelearning
0
8
43