Here is a collection of the best blogs, youtube, tweets and github repos in the field of Machine Learning, Deep Learning, Web Scrapping, Web applications, Chatbots and Mathematics.
- Web Scraping and Parsing HTML in Python with Beautiful Soup
- Mining Twitter Data with Python
- Scrape a Website with Scrapy and MongoDB
- How To Scrape With Python and Selenium WebDriver
- Which Movie Should I Watch using BeautifulSoup
- beginer-friendly Django tutorial
- Build a Microblog with Flask
- Create a Blog Web App In Django
- Choose Your Own Adventure Presentations
- Build a Todo List with Flask and RethinkDB
- Build a Todo List with Django and Test-Driven Development
- Build a RESTful Microservice in Python
- Microservices with Docker, Flask, and React
- Build A Simple Web App With Flask
- Build a RESTful API with Flask – The TDD Way
- Build a Reddit Bot
- How to Make a Reddit Bot - YouTube
- Build a Facebook Messenger Bot
- Making a Reddit + Facebook Messenger Bot
- How To Create a Telegram Bot Using Python
- Create a Twitter Bot In Python
- Learn Python For Data Science by Doing Several Projects:
- Write Linear Regression From Scratch in Python
- Step-By-Step Machine Learning In Python
- Predict Quality Of Wine
- Solving A Fruits Classification Problem
- Learn Unsupervised Learning with Python
- Build Your Own Neural Net from Scratch in Python
- Using Convolutional Neural Nets to Detect Facial Keypoints
- Generate an Average Face using Python and OpenCV
- Break A Captcha System using CNNs
- Use pre-trained Inception model to provide image predictions
- Create your first CNN
- Build A Facial Recognition Pipeline
- Build An Image Caption Generator
- Make your Own Face Recognition System
- Train a Language Detection AI in 20 minutes
- Object Detection With Neural Networks
- Learn Twitter Sentiment Analysis -
- Part I - Data Cleaning
- Part II - EDA, Data Visualisation
- Part III - Zipf's Law, Data Visualisation
- Part IV - Feature Extraction(count vectoriser)
- Part V - Feature Extraction(Tfidf vectoriser)
- Part VI - Doc2Vec
- Part VII - Phrase Modeling + Doc2Vec
- Part VIII - Dimensionality Reduction
- Part IX - Neural Nets with Tfdif vectors
- Part X - Neural Nets with word2vec/doc2vec
- Part XI - CNN with Word2Vec
- Use Transfer Learning for custom image classification
- Starting with Machine Learning
- Writing Research Paper
- Autoencoders
- Knowledge Distillation
- Spiral Classification
- Linear And Non Linear Transformations
- Style Transfer
- Simulated Annealing
- Learning Rate and Log Scale
- Overfitting High Accuracy
- Move on from Basic Problems
- MNIST in 3D
- Time-Series Models
- Lessons from a Data Problem
- Precision and Recall
- Ensemble Techniques
- Convolutions 1D 2D 3D
- Calculating Convolution Shapes
- Backpropagation Intuition
- PCA on Fashion MNIST
- Interpretation and Flexibility
- Irreducible Error
- Embedding Preprocessing in Model
- YOLO Object Detection
- Neural Nets as Combination of Linear Methods
- Validation vs Test Set
- R2 in Regression explained
- Regressions in 3D
- Residual Analysis
- Validation vs Test Set
- Apriori
- Multicollinearity
- Z-Score Explanation
- Segmentation Performance Measure
- Simple Spam Classifier
- Image Similarity Intuition
- Communication in Data Science
- Survival Bias Fallacy
- Survival Bias Story
- Feature Scaling
- Deployed Model Drift
- Dropout
- Logic Gates
- Feature Selection Elimination
- KMeans Clustering
- Feature Selection Types
- Normalization vs Standardization
- Machine Learning Jargon Part1
- Machine Learning Jargon Part2
- Computer Vision Skills
- One-Hot Encoding
- Keras Custom Generator
- Python Logger
- Sub List Operations
- Feature Importance
- Split and Join Keras Models
- Shuffle Arrays Synchronously
- Operations on Dates
- Splitting Joining Models
- Multiple Variable Assignment
- Ipython Cell Timing
- Decision Forests in Tensorflow
- Python Ellipsis
- Python Glob
- Set Operation for Data Curation
- Or as Short Circuit Operator
- Tensorflow Callbacks
- Zen of Python
- Existing Directories
- Eight Pandas Functions
- Function Annotation
- Corey Schafer Learning Resources
- Dict from Lists
- Reverse Dict
- System Command Run
- Confidence Interval Map
- Eval in Python
- Sorting Dictionaries
- Saving and Loading Numpy Arrays
- Raising Exceptions
- Args and Kwargs
- Useful Numpy Functions
- Joins in Pandas
- Merging Dictionaries
- Machine Learning Overview
- Machine Learning Algorithms Map
- Skills FOr Data Science
- Confusion Matrix
- Precision Vs Recall
- Precision Vs Recall Handdrawn
- Visualization Cheatsheet
- Accuracy Vs Precision
- Python Versatility
- Amazon Forecast
- Normal Distribution Summary
- Data Science Pyramid
- Decision Boundaries
- Statistics Concept Map
- Common Machine Learning Steps
- Neural Network Recognizes Dog
- Supervised Learning Flow