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What is Data Science ?
Data Science vs. Data Analysis vs. Data Engineering
Descriptive and Predictive Analytics
Data Science Life Cycle
Structured vs. Semi-Structured vs. Unstructured Data
Applications of Data Science
Applications in Healthcare and Recommender Systems
Image Analysis
Overview of Libraries
Beautiful Soup (Scraping Data from Simple HTML)
Beautiful Soup (Scraping Data from Html Table)
Scrapy
Numpy Basics
Numpy Array Creation
Numpy Array Manipulation
Sorting Numpy Arrays
Basic Statistics on Numpy Arrays
Broadcasting in Numpy Arrays
Pandas
Spacy Part 1
Spacy Part 2
Seaborn
Probability and Statistics
Probability
Statistics
Joint Probability
Conditional Probability and Bayes Theorem
Measures of Locations
Measures of Variability
Probability Distributions (Binomial and Bernoulli Distributions)
Gaussian Distribution
Poisson Distribution
Skewness and Kurtosis
Sampling Methods
Key Concepts in Statistics
Statistical Hypothesis Testing
Machine Learning Part-1
Machine Learning and its Types
Deep Learning and Recommender Systems
What is Regression ?
Univariate Linear Regression
Multivariate Linear Regression
Feature Scaling
Linear Regression in Scikit Learn
Regularization (Lasso, Ridge, and ElasticNet Regression)
Support Vector Regression
Nearest Neighbour Regression
Decision Tree Regression
Feature Engineering and Categorical Variables Encoding
Numerical Variables Transformation
Feature Selection (Filter Methods)
Feature Selection (Wrapper Methods)
Feature Selection (Intrinsic Methods)
Model Evaluation Measures (Explained Variance Score, MAE, MSE)
Model Evaluation Measures (Median Absolute Error, R^2 Score)
Dummy Regressors
Cross Validation
Case Study: House Prices Prediction using Advanced Regression
Machine Learning Part-2
Types of Classification Problems
Logistic Regression
Support Vector Machines
Decision Trees
Naive bayes Part-1
Naive bayes Part-2
K-Nearest Neighbors
Ensemble Learning Part 1
Ensemble Learning Part 2
XGBoost, Light GBM and CatBoost
Learning Curves
Model Evaluation Part 1
Model Evaluation Part 2
Dummy Estimators and Handling Imbalance Class Problem
Hyper-Parameter Optimization and Kaggle Competition
Machine Learning Part-3
Unsupervised Learning
K-Means Clustering
Hierarchical Clustering
DBSCAN Clustering and Customer Segmentation
Apriori Algorithm and Association Rules
Principal Component Analysis for Dimensionality Reduction
Semi-Supervised Learning Techniques
Deep Learning
What is Deep Learning?
Neural Networks
Feedforward Neural Networks
Backpropagation Part 1
Backpropagation Part 2
Convolutional Neural Network
Recurrent Neural Network
LSTM Networks
Machine Learning Tools and Libraries
Automated Machine Learning
Pandas Profiling and PyCaret
RAPIDS (Using GPU for Fast Computations)
Big Data Tools and Technologies
What is Big Data ?
Hadoop Ecosystem
Map Reduce Framework
Apache Spark and it's Components
Where to go next ?
Starting Career on Kaggle (Tips)
Recommended Courses from Educative
References and Acknowledgements
An Introductory Guide to Data Science and Machine Learning
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Numpy Array Manipulation
Numpy Array Manipulation
Let's cover more about Numpy arrays.
We'll cover the following...
Numpy array manipulation operations
np.array_split
np.column_stack
np.concatenate
np.hsplit
np.hstack
np.squeeze
np.vsplit
np.vstack
Coding Exercise
Numpy array manipulation operations
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