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Skills Covered in this Path
- Components of Data Science
- Data Science Architecture
- Skills needed to learn Python
- NumPy and Pandas libraries
- Python Basics
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Plotly
- Central Tendency
- Measures of Variability
- Measure of Skewness
- Kurtosis
- Hypothesis Testing
- T-test
- Probability
- Statistics
- Normal Distribution
- Sampling Distribution
- Hypothesis
- Central Limit Theorem
- Machine Learning Basics
- Supervised and unsupervised learning
- Algorithm basics
- K-Nearest Neighbour Algorithm
- Linear Regression Technique
- Naive Bayes Algorithm
- Support Vector Machines
- Random Forest Algorithm
- Linear Regression
- Logistic Regression
- Naïve Bayes
- ANN
- Tensorflow
- Keras
- Gradient
- Backpropagation
- Tensorflow
- Keras
- Neural Networks
- Linear Regression using Tensorflow
- MNIST Character Recognition
- Image classification using CNN