# ML Time

## **Improving the Aftermath Management of an Earthquake**

{% embed url="<https://omdena.com/projects/ai-earthquake/>" %}

## Happy Valentine's Day from MATLAB ❤️ Code ⬇️

{% embed url="<https://www.linkedin.com/posts/the-mathworks_2_happy-valentines-day-from-matlab-code-activity-6766687084829790208-XApw/>" %}

## 50+ Statistics Interview Questions and Answers for Data Scientists for 2021 <a href="#id-9320" id="id-9320"></a>

{% embed url="<https://towardsdatascience.com/50-statistics-interview-questions-and-answers-for-data-scientists-for-2021-24f886221271>" %}

## DIY- Multi-Level Dendrogram

{% embed url="<https://www.linkedin.com/posts/siddharth-pawar_vismydata-tableau-tableaudesktop-activity-6766344350101245952-kg0a/>" %}

## How to use ML to perform RF modulation recognition?

{% embed url="<https://www.linkedin.com/posts/james-heaton-66035310_xilinxvitis-tutorials-activity-6766037565733789696-XCft/>" %}

## Tools for building robust, state-of-the-art machine learning models

{% embed url="<https://thedataexchange.media/tools-for-building-robust-state-of-the-art-machine-learning-models/amp/>" %}

## English Audio Speech-to-Text Transcript with Hugging Face | Python NLP

[**https://www.linkedin.com/posts/amrrs\_english-audio-speech-to-text-transcript-with-activity-6766025732201287680-1DSy/**](https://www.linkedin.com/posts/amrrs_english-audio-speech-to-text-transcript-with-activity-6766025732201287680-1DSy/)

## **Neural Re-rendering for Full-frame Video Stabilization**

{% embed url="<https://alex04072000.github.io/NeRViS/>" %}

## AI-ML Cheat Sheets

{% embed url="<https://www.linkedin.com/feed/update/urn:li:activity:6765855868929089537/>" %}

## Q4 2020 Food Delivery & Rideshare Sales Report <a href="#adc7" id="adc7"></a>

{% embed url="<https://medium.com/edison-discovers/q4-2020-food-delivery-rideshare-sales-report-70382329c1b1>" %}

## AI PAPER SUMMARY

{% embed url="<https://www.marktechpost.com/category/tech-news/ai-paper-summary/>" %}

## Microservices Architecture at Netflix!

{% embed url="<https://www.linkedin.com/posts/srivathsan97_check-out-the-microservices-architecture-activity-6747814131904208896-ZdC2>" %}

## 10 Awesome Data Science Courses to make you an Awesome Data Scientist

{% embed url="<https://www.linkedin.com/feed/update/urn:li:activity:6765214718861938688/>" %}

## Yann LeCun’s Deep Learning Course

{% embed url="<https://www.linkedin.com/posts/imarpit_datascience-ml-machinelearning-activity-6765103006779260928-Z4t->" %}

## Analyzing seasonality with Fourier transforms using Python & SciPy

{% embed url="<https://www.linkedin.com/posts/theophano-mitsa-ph-d-2a62349_analyzing-seasonality-with-fourier-transforms-activity-6764900192136286208-D2HP>" %}

## An open-source text annotation tool for humans

{% embed url="<https://www.linkedin.com/posts/stevenouri_innovation-artificialintelligence-machinelearning-activity-6764884431628062720-X6_c>" %}

## PORORO: Platform Of neuRal mOdels for natuRal language prOcessing&#x20;

{% embed url="<https://www.linkedin.com/posts/montrealai_machinelearning-naturallanguageprocessing-activity-6764654087054102528-NgTz>" %}

## Indian Flag with Turtle using Python

&#x20;This Republic day I tried to do something creative and made an Indian Flag with Turtle using Python. Turtle is a pre-installed Python library. It enables users to create pictures and shapes by providing them with a virtual canvas.&#x20;

<https://www.linkedin.com/posts/ayushi7rawat_python3-githubcli-python-ugcPost-6759845965777125376-Il15>

You can also refer to the YouTube video tutorial for better understanding: [https://lnkd.in/dUrctgE](https://lnkd.in/dUrctgE?trk=public_post_share-update_update-text)&#x20;

GitHub Repo: [https://lnkd.in/disintQ](https://lnkd.in/disintQ?trk=public_post_share-update_update-text)&#x20;

Blog link: [https://lnkd.in/dcUuTgg](https://lnkd.in/dcUuTgg?trk=public_post_share-update_update-text)

## The Shiny AWS Book

{% embed url="<https://business-science.github.io/shiny-production-with-aws-book/?utm_content=buffere8902&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer>" %}

## 10 Most Stable Linux Distros In 2021

{% embed url="<https://analyticsindiamag.com/10-most-stable-linux-distros-in-2021/>" %}

## Python’s Pandas vs. R’s dplyr

{% embed url="<https://www.linkedin.com/redir/redirect?url=https%3A%2F%2Fwww%2Er-bloggers%2Ecom%2F2021%2F02%2Fpythons-pandas-vs-rs-dplyr-which-is-the-best-data-analysis-library%2F%3Futm_source%3Dfeedburner%26utm_medium%3Demail%26utm_campaign%3DFeed%253A%2BRBloggers%2B%2528R%2Bbloggers%2529&urlhash=qDJh&trk=public_post-content_share-article_title>" %}

## Top Ten Kaggle Notebooks For Data Science Enthusiasts In 2021

{% embed url="<https://analyticsindiamag.com/top-ten-kaggle-notebooks-for-data-science-enthusiasts-in-2021/>" %}

## An R package to build your resume or CV

{% embed url="<https://www.linkedin.com/posts/ludovicbocken_jaredlanderresumer-activity-6763816345650925569-3yGw>" %}

## Applied Data Science: Free E-Book

{% embed url="<https://www.linkedin.com/posts/mlindia_applied-data-science-free-e-book-activity-6763351573801308160-xLOp/>" %}

## &#x20;"The Data Engineering Cookbook" by Andreas Kretz!!

{% embed url="<https://www.linkedin.com/posts/imarpit_the-data-engineering-cookbook-by-andreas-activity-6763295036466626560-4itW/>" %}

## Data Cleaning

{% embed url="<https://www.linkedin.com/posts/udaykondreddy_data-cleaning-ugcPost-6762952860109033472-l_Ty>" %}

## Wind Forecast

{% embed url="<https://www.linkedin.com/posts/florianroscheck_flrscaisowindforecast-activity-6762438711935418368-sJci>" %}

## Fundamentals of Python Programming

{% embed url="<https://www.linkedin.com/posts/imarpit_fundamentals-of-python-programming-by-richard-activity-6762191400550359040-gMNa>" %}

## Mistakes to avoid as a Data Scientist

{% embed url="<https://www.linkedin.com/posts/learn-machine-learning_mistakes-to-avoid-activity-6762604522880806913-pTyz>" %}

## Fake AI generated blog

{% embed url="<https://www.linkedin.com/posts/mit-technology-review_a-college-kid-created-a-fake-ai-generated-activity-6762716435434225664-tflA>" %}

## ML Interview Questions

{% embed url="<https://www.linkedin.com/posts/imarpit_41-essential-machine-learning-interview-qnas-activity-6762550818743873536-VS9U>" %}

## BudgetML

{% embed url="<https://github.com/ebhy/budgetml>" %}

{% embed url="<https://www.linkedin.com/posts/hamzatahirofficial_ebhybudgetml-activity-6761958351417954304-gAdo>" %}

![](https://s3.amazonaws.com/MLMastery/MachineLearningAlgorithms.png?__s=75zixvk7vuhgu5yzxcim)

{% embed url="<https://flyyufelix.github.io/2016/10/08/fine-tuning-in-keras-part2.html>" %}

{% embed url="<https://jfgagne.ai/blog/the-canadian-ai-ecosystem-in-2018/>" %}

{% embed url="<https://jfgagne.ai/canadian-ai-ecosystem-2018-en/>" %}

![](https://i.redd.it/udk71f8496w01.png)

{% embed url="<https://towardsdatascience.com/why-we-switched-from-flask-to-fastapi-for-production-machine-learning-765aab9b3679>" %}

{% embed url="<https://www.linkedin.com/posts/stevenouri_artificialintelligence-datascience-deeplearning-activity-6678195852944781312-eLkq/>" %}

{% embed url="<https://towardsdatascience.com/a-flask-api-for-serving-scikit-learn-models-c8bcdaa41daa>" %}

{% embed url="<https://www.linkedin.com/posts/activity-6681140779710214144-vUa8/>" %}

{% embed url="<https://arxiv.org/abs/2001.11003>" %}

{% embed url="<https://github.com/UKPLab/kg2text>" %}

{% embed url="<https://www.linkedin.com/posts/stevenouri_augmentedreality-technology-datascience-activity-6681472315999498240-FRQu/>" %}

{% embed url="<https://www.linkedin.com/posts/activity-6681074002246590465-glkg/>" %}

{% embed url="<https://amp-cnn-com.cdn.ampproject.org/c/s/amp.cnn.com/cnn/2020/06/23/americas/ontario-math-curiculum-trnd/index.html>" %}

{% embed url="<https://medium.com/analytics-vidhya/morphological-processing-for-%E0%AE%A4%E0%AE%AE%E0%AE%BF%E0%AE%B4%E0%AF%8D-the-unsupervised-way-68afebc388c4>" %}

{% embed url="<https://pytorch.org/get-started/locally/>" %}

{% embed url="<https://www.youtube.com/playlist?app=desktop&list=PLYx7XA2nY5GfY4WWJjG5cQZDc7DIUmn6Z>" %}

{% embed url="<https://github.com/ChoudharyChanchal/game_control>" %}

{% embed url="<https://www.pyimagesearch.com/2020/07/13/r-cnn-object-detection-with-keras-tensorflow-and-deep-learning/>" %}

{% embed url="<https://medium.com/towards-artificial-intelligence/main-types-of-neural-networks-and-its-applications-tutorial-734480d7ec8e>" %}

{% embed url="<https://medium.com/analytics-vidhya/you-dont-understand-neural-networks-until-you-understand-the-universal-approximation-theorem-85b3e7677126>" %}

1-Introduction to Time Series and Forecasting <https://lnkd.in/gqZbe7p>

2-Statistics and Analysis of Scientific Data <https://lnkd.in/g-hbjWZ>

3-Linear Algebra Done Right <https://lnkd.in/gqCT-6g>

4-Linear Algebra <https://lnkd.in/gJSPXQd>

5-Algebra <https://lnkd.in/gc-H3Kk>

6-Understanding Analysis <https://lnkd.in/g_RXeVk>

7-Understanding Statistics Using R <https://lnkd.in/g27NnMy>

8-An Introduction to Statistical Learning <https://lnkd.in/gyjbQ-A>

9-Statistical Learning from a Regression Perspective <https://lnkd.in/g2gFWfi>

10-Robotics <https://lnkd.in/gJDEgec>

11-Regression Modeling Strategies <https://lnkd.in/gR3Mufh>

12-A Modern Introduction to Probability and Statistics <https://lnkd.in/gCgbX6m>

13-The Python Workbook <https://lnkd.in/gw4tAf7>

14-Machine Learning in Medicine — a Complete Overview <https://lnkd.in/g43uZiT>

15-Introduction to Data Science <https://lnkd.in/gSvtBCs>

16-Applied Predictive Modeling <https://lnkd.in/gcHus2e>

1. Data Science Process <https://pos.li/2fki4i>
2. Data Visualization in Business <https://pos.li/2fki4j>
3. Know Machine Learning Key Terminology <https://pos.li/2fki4k>
4. Understand Machine Learning Implementation <https://pos.li/2fki4l>
5. Machine Learning Applications on Marketing <https://pos.li/2fki4m> and Retail <https://pos.li/2fki4f>

{% embed url="<https://www.linkedin.com/pulse/canada-still-lead-ai-victor-anjos/>" %}

**TOP 10 SQL Concepts for Job Interview**

1. Aggregate Functions (SUM/AVG)
2. Group By and Order By
3. JOINs (Inner/Left/Right)
4. Union and Union All
5. Date and Time processing
6. String processing
7. Window Functions (Partition by)
8. Subquery
9. View and Index
10. Common Table Expression (CTE)

**TOP 10 Statistics Concepts for Job Interview**

1. Sampling
2. Experiments (A/B tests)
3. Descriptive Statistics
4. p-value
5. Probability Distributions
6. t-test
7. ANOVA
8. Correlation
9. Linear Regression
10. Logistics Regression

**TOP 10 Python Concepts for Job Interview**

1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming

{% embed url="<https://professional.uchicago.edu/find-your-fit/professional-education/certificate-programs-quantum-engineering-and-technology>" %}

{% embed url="<https://betakit.com/royal-bank-of-canada-borealis-ai-partner-with-red-hat-nvidia-on-new-ai-computing-platform/>" %}

{% embed url="<https://github.com/adityamhatre/GameCarControl-CV>" %}

{% embed url="<https://medium.com/@aditya.r.mhatre/car-controller-for-games-using-opencv-1ba821d5fe4b>" %}

{% embed url="<https://pydeck.gl/>" %}

{% embed url="<https://github.com/dheerajiiitv/T5-paraphrase-generation>" %}

{% embed url="<https://machinelearningtokyo.com/2020/07/26/10-cool-gpt-3-demos/>" %}

Data Science Topics: CRISP – DM - Project Management Methodology Exploratory Data Analytics (EDA) / Descriptive Analytics Statistical Data Business Intelligence and Data Visualization Plots & Inferential Statistics Probability Distributions (Continuous & Discrete) Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests Data Mining Supervised Learning – Linear Regression, OLS Predictive Modelling – Multiple Linear Regression Lasso and Ridge Regressions Logistic Regression – Binary Value Prediction, MLE Multinomial Regression Advanced Regression for Count Data Data Mining Unsupervised Learning - Clustering Data Mining Unsupervised Learning - Dimension Reduction (PCA) Data Mining Unsupervised Learning - Association Rules Recommendation Engine Network Analytics Machine Learning - k - NN Classifier Decision Tree & Random Forest Ensemble Techniques - Bagging and Boosting AdaBoost & Extreme Gradient Boosting Text Mining & Natural Language Processing (NLP) Machine Learning Classifier Technique - Naive Bayes Introduction to Perceptron, Multilayer Perceptron Building Blocks of Neural Network Deep Learning Black Box Technique - Neural Network Deep Learning Black Box Technique - SVM Survival Analytics Forecasting/Time Series – Model Driven Algorithms Forecasting/Time Series – Data Driven Algorithms

{% embed url="<https://microsoft.github.io/BLURB/index.html>" %}

{% embed url="<https://arxiv.org/abs/2007.15779>" %}

{% embed url="<https://www.dataschool.io/how-to-contribute-on-github/>" %}

{% embed url="<https://github.com/tiangolo/full-stack-fastapi-postgresql>" %}

{% embed url="<https://elitedatascience.com/>" %}

{% embed url="<https://arxiv.org/abs/2008.01533>" %}

{% embed url="<https://arxiv.org/pdf/2003.09040.pdf>" %}

{% embed url="<https://techcrunch.com/2020/05/29/tinyml-is-giving-hardware-new-life/?guccounter=1>" %}

{% embed url="<https://github.com/goru001/inltk>" %}

&#x20;

{% embed url="<https://inltk.readthedocs.io/en/latest/>" %}

{% embed url="<https://github.com/naiveHobo/InvoiceNet>" %}

{% embed url="<https://amaarora.github.io/2020/08/09/groupnorm.html#group-normalization-explained>" %}

{% embed url="<https://www.linkedin.com/posts/aroraaman_group-normalization-activity-6698343876433985536-Jadk/>" %}

{% embed url="<https://eng.uber.com/generative-teaching-networks/>" %}

{% embed url="<https://www.victorzhong.com/blog/getting-started-in-NLP-ML-research.html>" %}

{% embed url="<https://github.com/TDAmeritrade/stumpy>" %}

{% embed url="<https://stumpy.readthedocs.io/en/latest/>" %}

{% embed url="<https://seanmylaw.medium.com/stumpy-fdb9f8f1f261>" %}

{% embed url="<https://github.com/PettingZoo-Team/PettingZoo>" %}

{% embed url="<https://www.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r>" %}

{% embed url="<https://github.com/jim-schwoebel/allie>" %}

{% embed url="<https://www.borealisai.com/en/careers/employment/machine-learning-software-engineer/>" %}

<http://gvv.mpi-inf.mpg.de/projects/NHRR/> <http://gvv.mpi-inf.mpg.de/projects/NHRR/data/1415.pdf>

Machine Learning with Graphs, Leskovec&#x20;

{% embed url="<http://snap.stanford.edu/class/cs224w-videos-2019/>" %}

{% embed url="<https://www-technologyreview-com.cdn.ampproject.org/c/s/www.technologyreview.com/2019/08/02/131198/china-squirrel-has-started-a-grand-experiment-in-ai-education-it-could-reshape-how-the/amp/>" %}

1-The Elements of Statistical Learning <https://lnkd.in/gd-PpCa>

2-Introductory Time Series with R <https://lnkd.in/gemsHzv>

3-A Beginner’s Guide to R <https://lnkd.in/gwQ6m_B>

4-Data Structures and Algorithms with Python <https://lnkd.in/g9_djwr>

5-Introduction to Statistics and Data Analysis <https://lnkd.in/gUUJMCj>

6-Principles of Data Mining <https://lnkd.in/gMgmc-P>

7-Computer Vision <https://lnkd.in/gftqxf9>

8-Data Mining <https://lnkd.in/gJ6iugA>

9-Robotics, Vision and Control <https://lnkd.in/gq-q9i5>

10-Statistical Analysis and Data Display <https://lnkd.in/grCNSYq>

11-Statistics and Data Analysis for Financial Engineering <https://lnkd.in/gRn8zWd>

12-Stochastic Processes and Calculus <https://lnkd.in/gnWaWW6>

13Statistical Analysis of Clinical Data on a Pocket Calculator <https://lnkd.in/gM7VCgG>

14-Clinical Data Analysis on a Pocket Calculator <https://lnkd.in/gvxBvg6>

15-The Data Science Design Manual <https://lnkd.in/gKxgaRD>

16-An Introduction to Machine Learning <https://lnkd.in/gykPC2B>

{% embed url="<https://ai.googleblog.com/2020/08/on-device-real-time-body-pose-tracking.html>" %}

{% embed url="<https://towardsdatascience.com/slideio-a-new-python-library-for-reading-medical-images-11858a522059>" %}

{% embed url="<https://keras.io/examples/generative/cyclegan/>" %}

{% embed url="<https://towardsdatascience.com/text-generation-with-bi-lstm-in-pytorch-5fda6e7cc22c>" %}

{% embed url="<https://www.amazon.science/latest-news/machine-learning-course-free-online-from-amazon-machine-learning-university>" %}

{% embed url="<https://www.youtube.com/watch?t=40&v=FrbWQDdGpHQ&feature=youtu.be>" %}

{% embed url="<https://www.youtube.com/watch?t=270&v=K59cmobQKew&feature=youtu.be>" %}

{% embed url="<https://www.youtube.com/watch?t=407&v=HPU--yAGIBQ&feature=youtu.be>" %}

{% embed url="<https://bdtechtalks.com/2020/08/17/openai-gpt-3-commercial-ai/amp/>" %}

{% embed url="<https://github.com/HenriquesLab/ZeroCostDL4Mic>" %}

{% embed url="<https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki#contributors>" %}

{% embed url="<https://www.biorxiv.org/content/10.1101/2020.03.20.000133v3>" %}

{% embed url="<https://www.technologyreview.com/2020/08/18/1007196/ai-research-machine-learning-applications-problems-opinion/?utm_medium=tr_social&utm_campaign=site_visitor.unpaid.engagement&utm_source=LinkedIn#Echobox=1597721504>" %}

{% embed url="<https://www.pyimagesearch.com/2020/08/17/ocr-with-keras-tensorflow-and-deep-learning/>" %}

The Laplace Transform: A Generalized Fourier Transform&#x20;

{% embed url="<https://www.youtube.com/watch?v=7UvtU75NXTg&feature=youtu.be>" %}

{% embed url="<https://www.theverge.com/2020/8/18/21373335/faster-mri-scans-ai-machine-learning-facebook-nyu-research-clinical-study>" %}

{% embed url="<https://siliconangle.com/2020/08/19/microsoft-leads-16m-round-ai-data-science-startup-pachyderm/>" %}

{% embed url="<https://github.com/abhimishra91/insight>" %}

{% embed url="<https://github.com/DevashishPrasad/CascadeTabNet>" %}

&#x20;

{% embed url="<https://cvpr2020text.wordpress.com/>" %}

{% embed url="<https://colab.research.google.com/drive/1lzjbBQsF4X2C2WZhxBJz0wFEQor7F-fv?usp=sharing>" %}

{% embed url="<https://github.com/linkedin/detext>" %}

{% embed url="<https://dl.acm.org/doi/10.1145/3331184.3331381>" %}

{% embed url="<https://www.linkedin.com/pulse/all-cheatsheets-one-place-vipul-patel/>" %}

{% embed url="<https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.3556&rep=rep1&type=pdf>" %}

’Introduction to Statistics for Data Science, Exploratory Data Analysis in Python‘

Distributions

Probability Mass Functions

Cumulative distribution functions

Modeling distributions

Probability density functions

Relationships between variables

Estimation

Hypothesis testing

Linear least squares

Regression

Time series analysis

Survival analysis

Analytic methods

Credit: Allen B. Downey

{% embed url="<https://www.fast.ai/2020/08/20/soumith-forward/>" %}

{% embed url="<https://github.com/fastai/fastbook/blob/master/01_intro.ipynb>" %}

{% embed url="<https://github.com/fastai/fastbook>" %}

**XGBoost Tutorials:**&#x20;

<https://lnkd.in/g3dSRxz> \
1-Introduction to Boosted Trees \
2-Distributed XGBoost with AWS YARN \
3-Distributed XGBoost with XGBoost4J-Spark \
4-DART booster \
5-Monotonic Constraints \
6-Random Forests in XGBoost \
7-Feature Interaction Constraints \
8-Text Input Format of DMatrix \
9-Notes on Parameter Tuning \
10-Using XGBoost External Memory Version (beta)

{% embed url="<https://www.analyticsvidhya.com/blog/2018/09/an-end-to-end-guide-to-understand-the-math-behind-xgboost/>" %}

{% embed url="<https://www.kdnuggets.com/2018/03/catboost-vs-light-gbm-vs-xgboost.html>" %}

{% embed url="<https://github.com/rakesh4real/realtime-forex-api>" %}

<https://github.com/rakesh4real/fastapi-template> <https://realtime-forex.herokuapp.com/>

<https://www.mit.edu/~amidi/teaching/data-science-tools/> <https://github.com/shervinea/mit-15-003-data-science-tools>

<https://www.python-machinelearning.com/>

<https://guide.allennlp.org/overview>

{% embed url="<https://github.com/DevashishPrasad/CascadeTabNet>" %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://tactlabs.gitbook.io/featurepreneur/ml-time.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.