The articles have been categorised as follows:

👉 Video Tutorials

👉 Interview

👉 Mathematics for Machine/ Deep Learning

👉 Machine Learning

👉 Advanced Machine Learning

👉 Deep Learning ( Python )

👉 Capsule Neural Network

👉 Convolutional Neural Network

👉 Self Driving Car

👉 Tensorflow

👉 Chatbot

👉 Generative Adversial Network

👉 Courses

👉 Computer Vision

👉 Deploying Model

👉 Pytorch

👉 Natural Language Processing

👉 Recurrent Neural Network

👉 Miscellaneous

NO TIME TO READ AI RESEARCH? WE SUMMARIZED TOP 2018 PAPERS FOR YOU

• Intro to Deep RL by lexfridman

• DeepMindAI's Advanced DL and RL lectures:

• OpenAI's Deep RL workshop:

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• 7 Steps to crack your first Data Science Internship (Tips, Tricks and Resources!)

• Cracking the Machine Learning Interview

• What to Expect Interviewing for a Data Analyst Internship

• 45 Questions to test a data scientist on basics of Deep Learning (along with solution)

• The Most Comprehensive Data Science & Machine Learning Interview Guide You’ll Ever Need

• Data Science and Machine Learning Interview Questions ==================================++++++++++=====================================

• Linear Algebra for Machine Learning - All Parts

• Mathematics for Data Science

• Probability & Statistics for Data Science (Series)

• Singular Value Decomposition (SVD) Tutorial: Applications, Examples, Exercises

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• Naive Bayes in machine learning

• Regularization in Machine Learning

• Overfitting vs. Underfitting: A Complete Example

• Loss Functions and Optimization Algorithms. Demystified.

• L1 Norm Regularization and Sparsity Explained for Dummies

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• A Comprehensive Guide to Ensemble Learning (with Python codes)

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• How I implemented iPhone X’s FaceID using Deep Learning in Python.

• Generating Haiku with Deep Learning (Part 1)

• Detecting malaria using deep learning.

• How to do Deep Learning on Graphs with Graph Convolutional Networks

• Top 10 Pretrained Models to get you Started with Deep Learning (Part 1 – Computer Vision)

• A Comprehensive guide to Fine-tuning Deep Learning Models in Keras (Part I)

• A Comprehensive guide to Fine-tuning Deep Learning Models in Keras (Part II)

• Transfer learning & The art of using Pre-trained Models in Deep Learning

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• Understanding Hinton’s Capsule Networks. Part I: Intuition.

• Understanding Hinton’s Capsule Networks. Part 2. How Capsules Work.

• Understanding Hinton’s Capsule Networks. Part 3. Dynamic Routing Between Capsules.

• Understanding Hinton’s Capsule Networks. Part 4. CapsNet Architecture.

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• Building a Convolutional Neural Network (CNN) in Keras.

• Learn to build a Convolutional Neural Network on the web with this easy tutorial.

• CNN Architectures

• CNN Architectures 2

• Image Classification using Convolutional Neural Networks in Keras

• Convolutional Neural Networks with Data Augmentation using Keras

• Visualizing intermediate activation in Convolutional Neural Networks with Keras

• Eye in the Sky — Image Classification using Transfer Learning and Data Augmentation

• Detecting academics’ major from facial images

• Components of CNN

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• Building an Autonomous Vehicle Part 1: Using Behavioral Cloning to make a Self-Driving Car drive like yourself.

• Building an Autonomous Vehicle Part 2: Using Computer Vision to detect lane lines on road.

• Building an Autonomous Vehicle Part 3: Using Machine Learning techniques to detect vehicles on road.

• Building an Autonomous Vehicle Part 4.1: Sensor Fusion and Object Tracking using Kalman Filters.

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• Real-time Human Pose Estimation in the Browser with TensorFlow.js.

• How to play Quidditch using the TensorFlow Object Detection API.

• YOLO — You only look once, real time object detection explained.

• Hello world in Tensorflow.

• CIFAR-10 Image Classification in TensorFlow.

• Building an image caption generator with Deep Learning in Tensorflow

• Tensorflow: Beginners to Advanced (Kaggle kernel)

• Demystify the TensorFlow APIs

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• Getting started with Dialogflow and building my first bot (Newbie’s guide).

• Building a Conversational Chatbot for Slack using Rasa and Python -Part 1

• Building Your Own Chatbot Using DialogFlow

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• An intuitive introduction to Generative Adversarial Networks (GANs)

• Understanding Generative Adversarial Networks (GANs)

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• CS 188 | Introduction to Artificial Intelligence Fall 2018

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• Review: DeepMask (Instance Segmentation)

LearnOpenCV

• Deep learning based Object Detection and Instance Segmentation using Mask R-CNN in OpenCV (Python)

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• How to Deploy Machine Learning Models using Flask, Docker and Google Cloud Platform(GCP)

• Deploying Machine Learning Models with Docker

• Deploy anything to web in under 3 minutes

• Deploying a Simple Machine Learning Model in a Modern Web Application (Flask, Angular, Docker & Scikit-learn)

• A Flask API for serving scikit-learn models

• Machine learning on mobile devices: 3 steps for deploying ML in your apps

• Deploy ML/DL Models to Production via Panini

• Deploying Deep Learning Models On Web And Mobile ===================================++++++++++=====================================

• Get Started with PyTorch – Learn How to Build Quick & Accurate Neural Networks (with 4 Case Studies!)

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• [IMPORTANT] Evaluating Text Output in NLP: BLEU at your own risk

• An NLP View on Holiday Movies — Part II: Text Generation using LSTM’s in Keras

• Sentiment Analysis with Text Mining

• Natural Language Processing: Count Vectorization with scikit-learn

• Perfume Recommendations using Natural Language Processing

• (25-2-2019)An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec

• (25-2-2019)Classifying Tweets for Sentiment Analysis: Natural Language Processing in Python for Beginners

• Steps for effective text data cleaning (with case study using Python)

• Beginners Tutorial for Regular Expressions in Python

• Ultimate Guide to Understand & Implement Natural Language Processing (with codes in Python)

• A Must-Read NLP Tutorial on Neural Machine Translation – The Technique Powering Google Translate

• Introduction to StanfordNLP: An Incredible State-of-the-Art NLP Library for 53 Languages (with Python code)

• Introduction to Flair for NLP: A Simple yet Powerful State-of-the-Art NLP Library

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• Build a Recurrent Neural Network from Scratch in Python

• (24-02-2019)Fundamentals of Deep Learning – Introduction to Recurrent Neural Networks

• What is a Recurrent NNs and Gated Recurrent Unit (GRUS)

• Attention in Long Short-Term Memory Recurrent Neural Networks

• Understanding LSTM Networks

• Understanding LSTM and its diagrams

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• Here’s How Uber’s Ludwig Helps Deploy Code-Free DL Models