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Skills Covered in this Path
- NumPy Arrays
- NumPy Operations
- NumPy Math
- Saving & Loading NumPy
- Pandas Series
- Pandas DataFrame
- Pandas Functions (Mean
- Median
- Max
- Min)
- Data Manipulation
- Supervised Learning
- Unsupervised Learning
- Machine Learning with Python
- AI Fundamentals
- Python for AI
- Neural Networks Basics
- Biological vs. Artificial Neurons
- Perceptron Mechanism
- ANN Architecture
- Activation Functions
- Forward Propagation
- Loss Functions
- Keras Framework
- Gradient Descent
- MNIST Application
- TensorFlow
- Python
- Statistics
- Reinforcement learning
- Machine learning
- TensorFlow library
- Deep Learning
- Neural Networks
- Artificial Intelligence
- Image Classification
- Tensors
- Python
- ANN
- Tensorflow
- Keras
- Gradient
- Backpropagation
- Reinforcement Learning
- States
- Actions
- State based mechanism in Reinforcement Learning
- Tokenization
- Stemming
- Lemmatization
- Removing Stopwords
- Modeling Techniques in NLP
- Machine Learning and Logistic Regression
- Sentiment Analysis
- Functionalities of Textblob
- Textblob Sentiment Analysis
- U-Net
- Semantic Segmentation
- Data Analysis
- SQL
- SQL with Python
- Triggers
- Big Data basics
- Hadoop
- HDFS
- Hive basics
- Hive querying
- Hive data upload
- Hive simple operations
- Spark
- RDDs
- Hadoop
- Hadoop
- Spark
- Real-time Data Analytics
- Spark streaming
- NoSQL
- MongoDB
- Basic Overview of MongoDB
- R programming fundamentals
- variables
- data types
- data structures
- control structures
- functions
- packages
- importing data into R
- manipulating data in R
- performing statistical analysis in R
- data cleaning and wrangling
- statistical modeling
- HR Database Project
- DBMS
- RDBMS
- OpenCV
- Face Detection
- Face Recognition
- Deep Learning
- OpenCV Operations
- Face Detection demo
- Face Detection
- Face Recognition
- Applications of Face Recognition
- Face Detection using OpenCV using Python
