{"id":16083,"date":"2026-04-04T04:15:46","date_gmt":"2026-04-04T04:15:46","guid":{"rendered":"https:\/\/bvcoend.ac.in\/?page_id=16083"},"modified":"2026-04-04T04:15:46","modified_gmt":"2026-04-04T04:15:46","slug":"machine-learning-lab-ece","status":"publish","type":"page","link":"https:\/\/bvcoend.ac.in\/index.php\/machine-learning-lab-ece\/","title":{"rendered":"Machine Learning Lab – ECE"},"content":{"rendered":"[vc_row][vc_column width=”1\/4″][vc_wp_custommenu title=”Imp Links” nav_menu=”73″][\/vc_column][vc_column width=”3\/4″][vc_column_text]\n

Machine Learning Lab<\/span><\/h2>\n

The Machine Learning Lab provides practical exposure to the concepts and techniques used in designing intelligent systems. It focuses on implementing algorithms that enable computers to learn from data and make predictions or decisions without being explicitly programmed.<\/span><\/p>\n

In this lab, students work with various supervised and unsupervised learning algorithms such as linear regression, decision trees, support vector machines, and clustering techniques. The lab emphasizes hands-on experience using programming tools like Python along with libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib. Overall, the Machine Learning Lab helps students bridge the gap between theoretical knowledge and practical implementation, preparing them for applications in fields such as healthcare, finance, automation, and artificial intelligence.<\/span><\/p>\n

Course Objectives<\/span><\/h3>\n\n\n\n\n\n\n\n\n
Code<\/span><\/th>\nObjective<\/span><\/th>\n<\/tr>\n<\/thead>\n
C.OB-1<\/span><\/td>\nTo understand the need of machine learning<\/span><\/td>\n<\/tr>\n
C.OB2<\/span><\/td>\nTo learn about regression and feature selection.<\/span><\/td>\n<\/tr>\n
C.OB3<\/span><\/td>\nTo understand about classification algorithms.<\/span><\/td>\n<\/tr>\n
C.OB4<\/span><\/td>\nTo learn clustering algorithms<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Course Outcomes<\/span><\/h3>\n\n\n\n\n\n\n\n\n
CO<\/span><\/th>\nStatement<\/span><\/th>\nBlooms Level<\/span><\/th>\n<\/tr>\n<\/thead>\n
ML-407P.1<\/span><\/td>\nTo formulate machine learning problems<\/span><\/td>\nRemember, Analyze<\/span><\/td>\n<\/tr>\n
ML-407P.2<\/span><\/td>\nLearn about regression and feature selection techniques and develop applications based on the same.<\/span><\/td>\nRemember, Understand, Apply, Evaluate, Create<\/span><\/td>\n<\/tr>\n
ML-407P.3<\/span><\/td>\nApply machine learning techniques such as classification to practical applications.<\/span><\/td>\nUnderstand, Remember, Apply, Analyze<\/span><\/td>\n<\/tr>\n
ML-407P.4<\/span><\/td>\nApply Clustering algorithms to develop various practical applications.<\/span><\/td>\nUnderstand, Remember, Apply, Create<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Note:<\/strong> Enter correlation levels 1, 2 or 3 as defined below:<\/span>
\n1: Slight (Low) \u00a0\u00a0 2: Moderate (Medium) \u00a0\u00a0 3: Substantial (High)<\/span><\/p>\n

Correlation Table<\/span><\/h3>\n\n\n\n\n\n\n\n\n
CO<\/span><\/th>\nPO 1<\/span><\/th>\nPO 2<\/span><\/th>\nPO 3<\/span><\/th>\nPO 4<\/span><\/th>\nPO 5<\/span><\/th>\nPO 6<\/span><\/th>\nPO 7<\/span><\/th>\nPO 8<\/span><\/th>\nPO 9<\/span><\/th>\nPO 10<\/span><\/th>\nPO 11<\/span><\/th>\nPO 12<\/span><\/th>\nPSO 1<\/span><\/th>\nPSO 2<\/span><\/th>\n<\/tr>\n<\/thead>\n
CO1<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n
CO2<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n
CO3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n
CO4<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n3<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n–<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\"\"Facilities<\/span><\/h3>\n

Operating System \/ Software<\/span><\/h4>\n\n\n\n\n\n\n
Sr. No.<\/span><\/th>\nName<\/span><\/th>\nVersion<\/span><\/th>\n<\/tr>\n<\/thead>\n
1<\/span><\/td>\nWindows<\/span><\/td>\n20<\/span><\/td>\n<\/tr>\n
2<\/span><\/td>\nPython Anaconda<\/span><\/td>\nOpen<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Hardware Specifications<\/span><\/h4>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
S.No.<\/span><\/th>\nEquipment Name<\/span><\/th>\nSpecification<\/span><\/th>\nCount<\/span><\/th>\n<\/tr>\n<\/thead>\n
1<\/span><\/td>\nComputer System<\/span><\/td>\nIntel Core i9 10 Gen 2.10 GHz 32 GB RAM<\/span><\/td>\n1<\/span><\/td>\n<\/tr>\n
2<\/span><\/td>\nComputer System<\/span><\/td>\nIntel Core i5 4 Gen 2.10 GHz 16 GB RAM<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n
3<\/span><\/td>\nComputer System<\/span><\/td>\nIntel Core i7 8 Gen 3.10 GHz 8 GB RAM<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n
4<\/span><\/td>\nComputer System<\/span><\/td>\nIntel Core i5 10 Gen 2.10 GHz 8 GB RAM<\/span><\/td>\n27<\/span><\/td>\n<\/tr>\n
5<\/span><\/td>\nComputer System<\/span><\/td>\nGPU System<\/span><\/td>\n1<\/span><\/td>\n<\/tr>\n
6<\/span><\/td>\nPrinter<\/span><\/td>\nHP Laser Jet Pro P1108<\/span><\/td>\n1<\/span><\/td>\n<\/tr>\n
7<\/span><\/td>\nZYBO Board<\/span><\/td>\nZybo + Accessory Kit (410-279)<\/span><\/td>\n2<\/span><\/td>\n<\/tr>\n
8<\/span><\/td>\nZED Board<\/span><\/td>\nZed Board (410-248)<\/span><\/td>\n1<\/span><\/td>\n<\/tr>\n
9<\/span><\/td>\nGPU SYSTEM<\/span><\/td>\nIntel Xeon W-2245 RTX 2080 Ti GPU<\/span><\/td>\n1<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Staff<\/span><\/h3>\n