Niharmahesh commited on
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0ce1050
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1 Parent(s): ec7d27d

Update app.py

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  1. app.py +112 -13
app.py CHANGED
@@ -96,7 +96,6 @@ def display_work_experience():
96
  - This new habit aims to educate and inspire, bridging the gap between technical expertise and practical application in the modern data landscape.
97
  - Find my work on [Medium](https://medium.com/@nihar-palem) and [Substack](https://niharpalem.substack.com/publish/posts).
98
  """)
99
-
100
  def display_skills():
101
  st.title('Skills')
102
 
@@ -107,7 +106,9 @@ def display_skills():
107
  "Data Engineering",
108
  "Data Architecture",
109
  "Visualization",
110
- "Specialized Systems"
 
 
111
  ]
112
 
113
  # Create tabs
@@ -126,12 +127,20 @@ def display_skills():
126
  - Relational: MySQL, PostgreSQL
127
  - NoSQL: MongoDB
128
  - Data Warehouses: Snowflake, Redshift
 
129
 
130
  - **Development Tools**:
131
  - Version Control: Git, GitHub
132
  - Containerization: Docker
 
133
  - IDE: VS Code, PyCharm
134
  - Microsoft Office Suite
 
 
 
 
 
 
135
  """)
136
 
137
  # AI & Machine Learning
@@ -139,28 +148,36 @@ def display_skills():
139
  st.subheader("AI & Machine Learning")
140
  st.markdown("""
141
  - **Machine Learning Frameworks**:
142
- - PyTorch
143
  - TensorFlow
144
  - Scikit-Learn
145
  - XGBoost, Random Forest, AdaBoost
146
 
147
  - **Deep Learning**:
148
- - Vision Transformers
149
  - ResNet Architectures
150
  - Neural Networks
151
  - BiLSTM
152
 
153
- - **LLM & NLP**:
154
- - LLaMA-3 (70B/8B)
155
- - GPT-3.5
156
- - Sentence Transformers
157
- - Advanced Prompt Engineering
158
- - Multi-agent Architectures
 
159
 
160
  - **Computer Vision**:
161
  - MediaPipe
162
  - OpenCV
163
  - Image Processing Pipelines
 
 
 
 
 
 
 
164
  """)
165
 
166
  # Data Engineering & Cloud
@@ -168,7 +185,7 @@ def display_skills():
168
  st.subheader("Data Engineering & Cloud")
169
  st.markdown("""
170
  - **Cloud Platforms**:
171
- - AWS (Certified)
172
  - Google Cloud Platform (GCP)
173
  - Cloud Architecture Design
174
 
@@ -183,11 +200,14 @@ def display_skills():
183
  - Workflow Orchestration
184
  - Concurrent Processing
185
  - Real-time Data Streaming
 
186
 
187
  - **Infrastructure**:
188
- - CI/CD Pipelines
189
  - Infrastructure as Code
190
- -Kubernetes Basics
 
 
191
  """)
192
 
193
  # Data Architecture & Analytics
@@ -205,17 +225,21 @@ def display_skills():
205
  - Batch Processing
206
  - Time Series Analysis
207
  - Statistical Analysis
 
 
208
 
209
  - **Data Processing**:
210
  - Pandas, NumPy
211
  - Data Wrangling
212
  - Feature Engineering
213
  - Data Quality Assurance
 
214
 
215
  - **Performance Optimization**:
216
  - Query Optimization
217
  - Indexing Strategies
218
  - Caching Mechanisms
 
219
  """)
220
 
221
  # Visualization & Deployment
@@ -238,6 +262,7 @@ def display_skills():
238
  - Streamlit
239
  - Flask
240
  - Web Development
 
241
 
242
  - **Collaboration Tools**:
243
  - JIRA
@@ -273,6 +298,80 @@ def display_skills():
273
  - Computer Vision Systems
274
  - Time Series Forecasting
275
  - Anomaly Detection
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
276
  """)
277
 
278
  def display_articles():
 
96
  - This new habit aims to educate and inspire, bridging the gap between technical expertise and practical application in the modern data landscape.
97
  - Find my work on [Medium](https://medium.com/@nihar-palem) and [Substack](https://niharpalem.substack.com/publish/posts).
98
  """)
 
99
  def display_skills():
100
  st.title('Skills')
101
 
 
106
  "Data Engineering",
107
  "Data Architecture",
108
  "Visualization",
109
+ "Specialized Systems",
110
+ "Multimodal AI",
111
+ "LLM & Advanced AI"
112
  ]
113
 
114
  # Create tabs
 
127
  - Relational: MySQL, PostgreSQL
128
  - NoSQL: MongoDB
129
  - Data Warehouses: Snowflake, Redshift
130
+ - Vector Databases: FAISS, Pinecone
131
 
132
  - **Development Tools**:
133
  - Version Control: Git, GitHub
134
  - Containerization: Docker
135
+ - Orchestration: Kubernetes (Basic)
136
  - IDE: VS Code, PyCharm
137
  - Microsoft Office Suite
138
+
139
+ - **Frameworks & Libraries**:
140
+ - LangChain
141
+ - Hugging Face (Transformers, Diffusers)
142
+ - Scikit-Learn, Pandas, NumPy
143
+ - Apache Spark
144
  """)
145
 
146
  # AI & Machine Learning
 
148
  st.subheader("AI & Machine Learning")
149
  st.markdown("""
150
  - **Machine Learning Frameworks**:
151
+ - PyTorch (Advanced, PyTorch Distributed, DDP)
152
  - TensorFlow
153
  - Scikit-Learn
154
  - XGBoost, Random Forest, AdaBoost
155
 
156
  - **Deep Learning**:
157
+ - Vision Transformers (ViT)
158
  - ResNet Architectures
159
  - Neural Networks
160
  - BiLSTM
161
 
162
+ - **Distributed Training**:
163
+ - Multi-GPU Clusters (16+ GPUs)
164
+ - PyTorch DDP (Distributed Data Parallel)
165
+ - DeepSpeed
166
+ - Megatron
167
+ - CUDA Acceleration
168
+ - FlashAttention
169
 
170
  - **Computer Vision**:
171
  - MediaPipe
172
  - OpenCV
173
  - Image Processing Pipelines
174
+ - Satellite Imagery Analysis
175
+
176
+ - **Model Optimization**:
177
+ - Model Compression (Quantization, Distillation)
178
+ - Performance Optimization
179
+ - CUDA Programming
180
+ - Parallel Processing
181
  """)
182
 
183
  # Data Engineering & Cloud
 
185
  st.subheader("Data Engineering & Cloud")
186
  st.markdown("""
187
  - **Cloud Platforms**:
188
+ - AWS (Certified - Lambda, S3, Glue, EC2, Redshift)
189
  - Google Cloud Platform (GCP)
190
  - Cloud Architecture Design
191
 
 
200
  - Workflow Orchestration
201
  - Concurrent Processing
202
  - Real-time Data Streaming
203
+ - ThreadPoolExecutor Optimization
204
 
205
  - **Infrastructure**:
206
+ - CI/CD Pipelines (GitHub Actions)
207
  - Infrastructure as Code
208
+ - Kubernetes Basics
209
+ - Production Monitoring
210
+ - Distributed Training Clusters
211
  """)
212
 
213
  # Data Architecture & Analytics
 
225
  - Batch Processing
226
  - Time Series Analysis
227
  - Statistical Analysis
228
+ - A/B Testing
229
+ - Hypothesis Testing
230
 
231
  - **Data Processing**:
232
  - Pandas, NumPy
233
  - Data Wrangling
234
  - Feature Engineering
235
  - Data Quality Assurance
236
+ - Data Quality Management
237
 
238
  - **Performance Optimization**:
239
  - Query Optimization
240
  - Indexing Strategies
241
  - Caching Mechanisms
242
+ - SQL Performance Tuning
243
  """)
244
 
245
  # Visualization & Deployment
 
262
  - Streamlit
263
  - Flask
264
  - Web Development
265
+ - Hugging Face Spaces
266
 
267
  - **Collaboration Tools**:
268
  - JIRA
 
298
  - Computer Vision Systems
299
  - Time Series Forecasting
300
  - Anomaly Detection
301
+ - Real-time Web Scraping
302
+ - Automated Data Quality Checks
303
+ """)
304
+
305
+ # Multimodal AI
306
+ with tabs[6]:
307
+ st.subheader("Multimodal AI")
308
+ st.markdown("""
309
+ - **Vision-Language Models**:
310
+ - Qwen-VL
311
+ - Gemini Multimodal
312
+ - Vision-Language Understanding
313
+ - Cross-modal Fine-tuning
314
+ - Multimodal Evaluation
315
+
316
+ - **Visual AI**:
317
+ - Visual Question Answering (VQA)
318
+ - Vision Transformers (ViT)
319
+ - Stable Diffusion XL
320
+ - Generative AI (Vision)
321
+ - Image-Text Alignment
322
+
323
+ - **Multi-Agent Systems**:
324
+ - Multi-Agent Multimodal Workflows
325
+ - Strategic Agent Architecture
326
+ - Visual Agent Integration
327
+ - QA Agent Implementation
328
+
329
+ - **Evaluation & Testing**:
330
+ - Multimodal Benchmarking
331
+ - Cross-modal Bias Detection
332
+ - Performance Optimization
333
+ - Adversarial Testing
334
+ - Statistical Validation Methods
335
+ """)
336
+
337
+ # LLM & Advanced AI
338
+ with tabs[7]:
339
+ st.subheader("LLM & Advanced AI")
340
+ st.markdown("""
341
+ - **Large Language Models**:
342
+ - Fine-tuning (PEFT, LoRA, QLoRA)
343
+ - 2-Stage Training
344
+ - VLLM/LMMs
345
+ - Qwen, LLaMA (Llama-3.1-8B), GPT Integration
346
+
347
+ - **Advanced Techniques**:
348
+ - Prompt Engineering (Advanced, Context Injection)
349
+ - RAG (Retrieval-Augmented Generation)
350
+ - LLM Evaluation Benchmarking
351
+ - LLM-as-judge
352
+ - Auto Hinter Systems
353
+
354
+ - **Production AI Systems**:
355
+ - Multi-Agent Systems
356
+ - API Integration
357
+ - Performance Optimization
358
+ - Tenstorrent Hardware Utilization
359
+ - MLOps
360
+
361
+ - **Specialized Applications**:
362
+ - Semantic Job Matching
363
+ - Resume Generation
364
+ - Marketing Campaign Automation
365
+ - Infrastructure Change Detection
366
+ - Exercise Pose Correction
367
+
368
+ - **AI Testing & Validation**:
369
+ - Unit/Integration Testing for AI
370
+ - Offline Evaluation Frameworks
371
+ - Model Validation
372
+ - ROC Curve Analysis
373
+ - RMSE Validation
374
+ - Bias Mitigation
375
  """)
376
 
377
  def display_articles():