Machine Learning:
Basics:

Ridge and Lasso Regression: L1 and L2 Regularization. Basics of regularization techniques in regression with examples. Library: ScikitLearn.

A Simple Example of Pipeline in Machine Learning with Scikitlearn. Grid Search CrossValidation & Sklearn Pipeline

Principal Component Analysis and SVM in a Pipeline with Python. Sklearn Pipeline, GridSerchCV and visualizing SVM decision boundary.

Interpreting Data through Visualization with Python Matplotlib. Next level interpretable data visualization. Libraries: Matplotlib & Seaborn

Opening a Restaurant in Tokyo. How to get started with a datascience project. Collecting and cleaning data to visualization + machine learning applications. Libraries: Pandas, Sklearn, Seaborn etc.
Understanding Fundamental Algorithms:

Support Vector Machines. Lagrange Multipliers & Decision Boundary Condition.

DBSCAN Algorithm: Complete Guide and Application with Python ScikitLearn. Clustering spatial database and example using Canada weather station data.

Understanding Decision Tree Classification with ScikitLearn. Gini Index, Pipeline and GridSearchCV. Understand which feature is more important and how it’s chosen.

Logistic Regression and Logits. How to think of logistic regression starting from linear Regression.
Probabilistic Approach:

Full Review of Expectation Maximization Algorithm. ELBO, KL Divergence and Gaussian Mixture Models.

Bayesian Neural Network: Epistemic and Aleatoric Uncertainty. What are aleatoric and epistemic uncertainties? How to include uncertainties in a neuralnet model prediction?

Normalizing Flows: Getting Started and Transforming Probability Distributions. What is a normalizing flow? How do we transform between probability distributions using bijective transformations?

Masked Autoregressive Flow: Implementing with TFProbability. Triangular matrices are so cool!
Deep Learning :
Basics & Hands On:

Build Better and Faster Image Pipelines with
tf.data
. WhyImageDataGenerator
may die soon? 
Class Imbalance & Focal Loss. Application of Focal Loss using TensorFlow.

Paper Review: General and Adaptive Robust Loss Function. A loss function that can adapt during training?

Vision Transformer. What is selfattention and implementing ViT from scratch using TensorFlow 2.0
Applications:

Facial Keypoints Detection: Image and Keypoints Augmentation. Inception like network and augmentation of image and keypoints using Imgaug library.

MultiClass Classification: Cassava Leaf Disease: Case Study. Deploy a pretrained InceptionRensetV2 for leaf disease classification.

Chest Xray & Pneumonia: Deep Learning with TensorFlow. ClassImbalance, Data standardization, and AUCROC metric for evaluation.

Understand and Implement ResNet50 with TensorFlow 2.0. A very deep dive to understand why residual connection is so cool and build Resnet from scratch using TensorFlow.

How Deep Neural Networks Look for Features in Images?. Visualize what’s happening in the hidden layers using TensorFlow, Keras.

Facebook Just Launched the Coolest Augmentation Library: Augly.
Quantum Computing :
Basics :
 Simple Gates and Implementations Using Qiskit.
 Bell State & Entanglement with Qiskit.
 Uniform Superposition in Quantum Computing.
 Love Story of Alice & Bob: Teleportation.
 Density Matrix and Bloch Sphere. How are they connected with Pauli Spinors?
Algorithms & Implementations:
 DeutschJozsa Algorithm: Balanced or Constant Function?.
 Grover’s Algorithm: Unstructured Search.
 Quantum Fourier Transform: Implement with Qiskit.
 Quantum Phase Estimation: Application of QFT. Phase kickback & step by step explanation of QPE circuit! Implementation using Qiskit.
 Shor’s Algorithm. Factoring prime numbers using quantum computer & how period finding is related with factoring numbers?