🔻Top 10 Deep Learning Projects on #Github

The top 10 #deep_learning projects on Github include a number of #libraries, #frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.
1. Caffe
2. Data Science IPython Notebooks
3. ConvNetJS
4. Keras
5. MXNet
6. Qix
7. Deeplearning4j
8. Machine Learning Tutorials
9. DeepLearnToolbox
10. LISA Lab Deep Learning Tutorials

link: https://www.kdnuggets.com/2016/01/top-10-deep-learning-github.html

📌Via: @cedeeplearning

🔻Top 10 Statistics Mistakes Made by Data Scientists

🔹by Norman Niemer

The following are some of the most common statistics mistakes made by data scientists. Check this list often to make sure you are not making any of these while applying statistics to data science.

1. Not fully understanding the objective function

2. Not having a hypothesis on why something should work

3. Not looking at the data before interpreting results

4. Not having a naive baseline model

5. Incorrect out-sample testing

6. Incorrect out-sample testing: applying preprocessing to full dataset

7. Incorrect out-sample testing: cross-sectional data & panel data

8. Not considering which data is available at point of decision

9. Subtle Overtraining

10. "need more data" fallacy
——————————
📌Via: @cedeeplearning
📌Other social media: https://linktr.ee/cedeeplearning

link: https://www.kdnuggets.com/2019/06/statistics-mistakes-data-scientists.html

#datascience
#machinelearning
#statistics
#github

📕 GPT-3: Language Models are Few-Shot Learners

⚪️ Github: https://github.com/openai/gpt-3

🔹Paper: https://arxiv.org/abs/2005.14165v1
———————
📌 Via: @cedeeplearning

#machinelearning #math
#deeplearning #neuralnetworks
#datascience #paper #github